System and method for producing parametric maps of optoacoustic data

ABSTRACT

A method is disclosed for creating and outputting a masked parametric map (e.g., hemoglobin oxygenation) that reflects parameters in a first parametric map (e.g., relative oxygenation) and second parametric map (e.g., relative hemoglobin). In an illustrative embodiment, the method comprises a steps of generating a first parametric map, generating a second parametric map, and then generating a masked parametric map that reflects parameters in the first and second parametric maps. The masked map may present information not readily apparent from the first parametric map and the second parametric map, and not obtainable from the first and second parametric maps independently. The first parametric map may be based upon portions of two optoacoustic images created using differing wavelengths of light. The first parametric map is reflective of areas within the volume of tissue that have a differing response to the longer wavelength light event compared to the shorter one. The second parametric map is reflective of areas within the volume of tissue that have a stronger response to the longer and shorter wavelength light events than the surrounding areas. A masked parametric map is output which is reflective of a combination of information in the first and second parametric maps. In an embodiment, the masked parametric map is generated by generating a mask reflective of a combination of information in the first and second parametric maps, and applying the mask to one of the first or second parametric maps to form the masked parametric map. In an embodiment, one or more of the parametric maps is coregistered with, and overlayed on an ultrasound image of the same volume of tissue before being output.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. patent applicationSer. No. 13/507,222, filed Jun. 13, 2016, entitled “SYSTEM AND METHODFOR PRODUCING PARAMETRIC MAPS OF OPTOACOUSTIC DATA”, the disclosure ofwhich is hereby incorporated herein by reference.

REFERENCE TO COMPUTER PROGRAM LISTING APPENDIX

A computer program listing appendix is submitted herewith on one CD-ROMand one duplicate CD-ROM. The total number of CD-ROMs includingduplicates is two. The file on the CD-ROMs is named “Appendix.txt”, wascreated on Jun. 12, 2012, and is 104,448 bytes in length. The materialon the CD-ROM is incorporated by reference herein.

This application includes material which is subject to copyrightprotection. The copyright owner has no objection to the facsimilereproduction by anyone of the patent disclosure, as it appears in thePatent and Trademark Office files or records, but otherwise reserves allcopyright rights whatsoever.

FIELD

The present invention relates in general to the field of medicalimaging, and in particular to system relating to optoacoustic imaging.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, features, and advantages of theinvention will be apparent from the following more particulardescription of preferred embodiments as illustrated in the accompanyingdrawings, in which reference characters refer to the same partsthroughout the various views. The drawings are not necessarily to scale,emphasis instead being placed upon illustrating principles of theinvention.

FIG. 1 shows a schematic block diagram illustrating an embodiment of acombined optoacoustic and ultrasound system that may be used as aplatform for the methods and devices disclosed herein.

FIG. 2 shows a flow for an illustrative embodiment of a method ofproviding output images resulting from optoacoustic data, and fromoptoacoustic data combined with ultrasound data.

FIG. 3 shows a flow for an illustrative embodiment of a method forpreprocessing sinograms to remove unwanted information.

FIG. 4 shows a flow for an illustrative embodiment of a method for imagereconstruction.

FIG. 5 shows a flow for an illustrative embodiment of a method ofpost-processing to produce an envelope image.

FIG. 6 shows a flow for an illustrative embodiment of a method ofperforming fluence compensation.

FIG. 7 shows a flow for an illustrative embodiment of a method ofcreating color parametric maps from the envelope image information.

FIG. 8 shows a flow for an illustrative embodiment of a method of motionand tracking processing.

FIG. 9 shows a flow for an illustrative embodiment of a method ofproducing grayscale parametric maps from envelope image information.

FIGS. 10-12 show an illustrative four-image displays with parameterinput and display.

FIGS. 13-15 show illustrative six-image displays.

FIG. 16 shows a schematic orthogonal view of an embodiment of a probethat may be used in connection with the methods and other devicesdisclosed herein.

FIG. 17 shows an exploded view of an embodiment of the probe shown inFIG. 16.

FIG. 18 shows a cutaway view taken along the centerline of the widerside of the probe shown in FIG. 16.

FIG. 19A is a side view not-to scale diagrammatic two dimensionalrepresentation of light exiting an optical fiber.

FIG. 19B shows an end view of a light pattern that may result on asurface from placement of optical fibers directly on to that surface.

FIG. 20A shows an end view of a desirable light pattern for use inconnection with the optoacoustic techniques discussed herein.

FIG. 20B shows a side view diagrammatic representation of an effect of aground glass beam expander on the light emitting from a fiber shown inFIG. 19A.

FIG. 20C shows a side view diagrammatic representation of an effect of aconcave lens beam expander on the light emitting from a fiber shown inFIG. 19A.

FIG. 21 is a representation of a phantom with a variety of targetstherein that may be used in connection with calibration and testing ofan optoacoustic device.

FIG. 22 is a representation of an active phantom that may be used inconnection with calibration and testing of an optoacoustic device.

FIG. 23 is a representation of another phantom with a variety of targetstherein that may be used in connection with calibration and testing ofan optoacoustic device.

FIGS. 24A-24C show schematic orthogonal views of alternative embodimentsof a probe that may be used in connection with the methods and otherdevices disclosed herein.

FIGS. 25A-25C show a representation of several examples of variousorganizations of two dimensional arrays of transducer elements.

FIG. 26 is an illustrative example of a two-armed forceps-like probehaving transducer arrays on its arms which can be physically positionedusing finger grips.

FIG. 27 is an illustrative example of a two-armed forceps-like probehaving a transducer array on one arm and a light source on the other foruse in forward transmission mode.

FIG. 28 is a schematic block diagram illustrating hardware components ofthe system.

FIG. 29 is a block diagram illustrating the illumination subsystem andcontrol interfaces of the system in accordance with an embodimentthereof.

FIG. 30 is a pulse diagram illustrating a radiation restriction in thesystem.

FIG. 31 is a schematic block diagram of one embodiment of a foot switchclosure.

While the invention is amenable to various modifications and alternativeforms, specifics thereof have been shown by way of example in thedrawings and will be described in detail. It should be understood,however, that the intention is not to limit the invention to theparticular embodiments described. On the contrary, the intention is tocover all modifications, equivalents, and alternatives falling withinthe spirit and scope of the invention.

DETAILED DESCRIPTION

The following description and drawings are illustrative and are not tobe construed as limiting. Numerous specific details are described toprovide a thorough understanding. However, in certain instances,well-known or conventional details are not described in order to avoidobscuring the description. References to one or an embodiment in thepresent disclosure are not necessarily references to the sameembodiment; and, such references mean at least one.

Reference in this specification to “one embodiment” or “an embodiment”means that a particular feature, structure, or characteristic describedin connection with the embodiment is included in at least one embodimentof the disclosure. The appearances of the phrase “in one embodiment” invarious places in the specification are not necessarily all referring tothe same embodiment, nor are separate or alternative embodimentsmutually exclusive of other embodiments. Moreover, various features aredescribed which may be exhibited by some embodiments and not by others.Similarly, various requirements are described which may be requirementsfor some embodiments but not other embodiments.

The systems and methods are described below with reference to, amongother things, block diagrams, operational illustrations and algorithmsof methods and devices to process optoacoustic imaging data. It isunderstood that each block of the block diagrams, operationalillustrations and algorithms and combinations of blocks in the blockdiagrams, operational illustrations and algorithms, can be implementedby means of analog or digital hardware and computer programinstructions.

These computer program instructions can be provided to a processor of ageneral purpose computer, special purpose computer, ASIC, or otherprogrammable data processing apparatus, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, implements the functions/acts specified inthe block diagrams, operational block or blocks and or algorithms.

In some cases frequency domain based algorithms require zero orsymmetric padding for performance. This padding is not essential todescribe the embodiment of the algorithm so it is sometimes omitted fromthe description of the processing steps. In some cases, where padded isdisclosed in the steps, the algorithm may still be carried out withoutthe padding. In some cases padding is essential, however, and cannot beremoved without corrupting the data.

In some alternate implementations, the functions/acts noted in theblocks can occur out of the order noted in the operationalillustrations. For example, two blocks shown in succession can in factbe executed substantially concurrently or the blocks can sometimes beexecuted in the reverse order, depending upon the functionality/actsinvolved.

Reference will now be made in more detail to various embodiments of thepresent invention, examples of which are illustrated in the accompanyingdrawings and the Appendix. As will be apparent to one of skill in theart, the data structures described in the Appendix and processing stepsdescribed in the Appendix (including in pseudo-code) may be implementedin a variety of other ways without departing from the spirit of thedisclosure and scope of the invention herein. The Appendix is intendedto provide one manner of implementing the concepts disclosed herein thepurpose of illustration and to facilitate understanding.

System and Method for Presenting Optoacoustic Data

Turning to FIG. 1, and as described generally below under the headingOptoacoustic System and Method is a device 100, including a probe 102connected via a light path 132 and an electrical path 108 to a systemchassis 101. Within the system chassis 101 is housed a light subsystem129 and a computing subsystem 128. The computing subsystem 128 includesone or more computing components for, among other things, optoacousticcontrol and analysis. In an embodiment, through the sampling oftransducers in the probe 102, the device 100 can obtain data received inresponse to: stimulation caused by pulsed light sources 130, 131 (i.e.,the optoacoustic return signal); and to stimulation caused by acousticoutput of the ultrasound transducer elements.

In an embodiment, to obtain an optoacoustic return signal correspondingto a single light event occurring in a volume of tissue, the transducersin the probe 102 can be sampled for a period of time after the lightevent. In an embodiment, the transducers in the probe 102 can be sampledfor a period of time after the light event approximately equal to thetime it would take sound to travel a desired distance in the tissue. Inan embodiment, the desired distance may be at least one centimeter. Inan embodiment, the desired distance may be at least two centimeters. Inan embodiment, the period of sampling would correspond to the amount oftime it would take sound to travel at least one, but not more than 15centimeters in tissue. In an embodiment, the period of sampling wouldcorrespond to the amount of time it would take sound to travel at leastfive, but not more than 12 centimeters in tissue. In an embodiment, thedesired distance may be less than one centimeter. The sampling rateshould be sufficient to obtain sufficient information in theoptoacoustic return signal. In an embodiment, the sampling rate is above20 Mhz, in another embodiment, the sampling rate is above about 30 Mhz.In an embodiment the sampling is at least 8 bits, and more preferablymore than 12 bits. In an embodiment, sampling is done at 14 bits. In anembodiment, sampling is done at resolutions higher than 14 bits.

In an exemplary embodiment, to obtain the optoacoustic return signal,128 or 256 transducers (i.e., channels) in a probe 102 are sampled at 14bits for approximately 65 microseconds (μs) at a sampling rate of 31.25Mhz. The 65 μs of sampling at 31.25 Mhz results in over 2,000 samples.In an embodiment, 2,045 14 bit samples may be stored for each transduceror channel. For efficiency, the 14 bit samples can be stored in a 16 bitcomputer word. The samples associated with a single light event, alongwith additional header information relating to the light event, can bestored in a frame of about 512 KB (kilobytes) for 128 channels, or 1 MB(megabyte) for 256 channels. Thus, in an exemplary embodiment, theoptoacoustic return signal from a light event, including headerinformation, can be stored in either 512 KB, or 1 MB. As discussedfurther below, in an embodiment, the device 100 comprises at least twolight sources 130, 131 operating at different light wavelengths. In anembodiment with two light sources 130, 131 operating at different lightwavelengths, the optoacoustic return signal from one light event fromeach of the light sources can be used in the method and system forpresenting the optoacoustic data. In an embodiment, the device 100comprises a single light source that may be operated at differentwavelengths, such as a tunable laser that can change wavelengths quicklyenough for use as described herein. In an embodiment, the device 100comprises at least two light sources 130, 131, each being capable oftuning to a plurality of different wavelengths. In an embodiment, thedevice 100 comprises one light source 130 operating a one lightwavelength, and at least one additional light source 131 capable ofbeing tuned to a plurality of different wavelengths.

As used herein, the term sinogram refers to sampled data or processedsampled data corresponding to a single light event. The term sinogram isalso used at times to refer to an image presented by using the originalor filtered sampled data as gray scale or color data, wherein there is acorrespondence between the samples in the data and the voxels in theimage. In an embodiment using optoacoustic return signals from twodifferent light events, each corresponding to a different wavelength oflight, the term short sinogram refers to the sinogram corresponding tothe shorter wavelength of light generating a light event, and the termlong sinogram refers to the sinogram corresponding to the longerwavelength of light generating a light event. Because more than twodifferent wavelengths may be used, the use of the terms short and longwavelength are intended to embody the extended context of a system withan arbitrary number of wavelengths.

In an embodiment, as discussed in more detail below, sinograms areprocessed to produce an envelope image. As used herein the term shortenvelope image refers to an envelope image corresponding to the shortsinogram, and the term long envelope image refers to an envelope imagecorresponding to the long sinogram. In an embodiment, the short sinogramand long sinogram are each processed separately to produce a shortenvelope image and a long envelope image, respectively. The short andlong envelope images are then used together to generate parametricimages. From the parametric images, maps can be created of oxygenation,hemoglobin and masked oxygenation. These maps can be co-registered datarepresenting an ultrasound image of substantially the same volume, andcan thereafter produce one or more of an oxygenation image, a hemoglobinimage and a masked oxygenation image. In an embodiment, the oxygenationimage, hemoglobin image and masked oxygenation image reflect informationabout the composition of the volume of tissue. The terms parametric mapand parametric image are in some instances used interchangeably. The useof the term map generally relates to the correspondence between theimage and a volume. Parametric maps may be represented in numerous ways,including, for example, as a single-channel (i.e., grayscale)representation, as a color (i.e., RGB) representation, or as a colorwith transparency (RGBA) representation. Parametric maps may be used toconvey qualitative or quantitative information about one or moreparameters. A parametric map or parametric image may be represented incomputer memory or presented as a displayed representation, thus, asused herein, the term “image” or “map” do not necessarily imply a visualrepresentation.

Storing Sinogram and Other System Data

In an embodiment, the sinogram, along with other data recorded relatingto the use of the optoacoustic device, may be recorded in a laser opticmovie file or LOM. The LOM is not, as the name would suggest, a moviefile, but rather, the LOM is a collection of recorded data that may berecorded in group of related files, or more preferably, in a single datafile. One consideration for the format of the LOM is the differing andlikely asynchronous processes that generate data requiring storage inthe LOM. In an embodiment, the LOM can be used to store a variety ofinformation concerning the use of the optoacoustic device, including,without limitation, the long and short optoacoustic sinograms,ultrasound frames, configuration data, annotations made by a user, or ata later time, an audio and/or video recording made during the use of theoptoacoustic device and information concerning version information asreported by the optoacoustic system and its software.

In an embodiment, the LOM may be structured in blocks of 1024 bytes (1K)each. Each collection of information (e.g., a sinogram) may comprise aheader, and, where additional data is required, one or more additionalblocks of information associated with the header. In an embodiment, theheader may include an identifier that is used to identify the block as aheader. In an embodiment, the header may also include a value for asynchronization counter to permit the collection of information to beplaced in proper order when the LOM is used, even if it is recorded inthe LOM out of order, as may be the case with the varied types of inputsand I/O systems in a particular implementation. In an embodiment, theheader further comprises a CRC of itself and any additional dataassociated with the collection, thus permitting an integrity check orvalidation of the entire collection within the LOM. A data structure foran exemplary LOM is provided in the Appendix.

Processing Sinograms

For a variety of reasons, sinograms may contain unwanted, inaccurate orinsufficiently scaled data. These maladies of sinogram data may resultfrom myriad reasons, including characteristics of the measuringinstrument (e.g., the probe) or the light used, characteristics of thevolume (i.e., the tissue), characteristics of the interaction betweenthe volume and the probe or light, external stimuli, or other sources.Regardless of the source, a variety of processes can be used to removeunwanted aspects of the sinogram data.

In an exemplary embodiment, where the sinogram data is sampled as aninteger, e.g., as a 14 bit integer, prior to performing the processingsteps on the sinogram, the sinogram data may be converted from integerform to a floating point number. Conversion from integer to floatingpoint is performed to increase accuracy and expand the dynamic range ofthe calculations. In an embodiment, the sinogram may be processed asinteger data. In an embodiment, the sinogram may be processed as integerdata, but the integers are enlarged to a sufficient size to accommodatethe appropriate range of data, e.g., 64 bits, or 96 bits, or 128 bits.

Generally in each of the following steps for processing the sinogram,the processing is performed on the time domain signal. In a preferredembodiment (and as discussed below) the probe 102 includes an acousticlens that enables the sinogram data to be more focused on what is on theplane below that of the transducers—the image plane. In an embodiment,the probe comprises an acoustic lens having a focal length of between 10and 40 millimeters. In an illustrative embodiment, the probe comprisesan acoustic lens having a focal length of 20 millimeters. In anembodiment, the probe may comprises an acoustic lens having a focallength that can be zoomed in or out, in hardware, or in software.

As discussed above, in an illustrative embodiment, each channel of thesinogram data represents approximately 100 millimeters of distance inthe volume. The acoustic lens generally rejects at least some portion ofa signal propagating from points outside (e.g., orthogonal) to the imageplane. Each transducer, however, receives signal from substantially allpoints of the image plane that lie within the approximately 100millimeters distance. The received signal for a channel can be thoughtof as comprising the area of a semicircle of radius 100 on the imageplane.

Turning to FIG. 2, an overview of an exemplary process is shown,beginning with the acquisition of three sets of data, namely, a shortsinogram (step 205), a long sinogram (step 210) and an ultrasound image(step 215), and processing the data to produce up to six separate imagesthat may be useful in viewing various aspects of that acquired data. Inan exemplary embodiment, the three sets of acquired data may be acquiredusing a handheld optoacoustic probe 102 (FIG. 1). For the purposes ofillustration herein, it may be presumed that probe 102 movement isminimal, if any, between the acquisition of the three sets of data insteps 205, 210 and 215. In an exemplary embodiment, a reasonable framerate (e.g., 10 hz), coupled with a reasonably steady hand used inhandholding the probe may yield the three data sets having substantiallyminimal movement occurring there-between. It should be noted that theprocess described herein is not limited to being used with the threeidentified data sets. Use of additional data sets, such as, for example,data sets from additional wavelengths of light, may be used to furtherimprove the resulting images.

As will be discussed in more detail below, the short and long sinogramdata are preprocessed (step 220) in one or more separate manners toreduce or compensate for undesired data in the sinogram, includingcharacteristics of the measuring instrument (e.g., the probe) or thelight used, characteristics of the volume (i.e., the tissue),characteristics of the interaction between the volume and the probe orlight, external stimuli, or other sources. After the preprocessing,separate short and long images are reconstructed (step 225). In anembodiment, separate real and imaginary components of complex short andlong images result from the reconstruction step. In an embodiment, theprocessing (step 230) of the reconstructed images is performed. Theprocessing (step 230) may remove additional artifacts that can beidentified in the reconstructed images, and in any event creates a shortenvelope image (232) and a long envelope image (234). In an embodiment,the short and long envelope images (232, 234) are used to generateparametric images (step 240) process. The generate parametric images(step 240) process outputs an oxygenation map (250), a hemoglobin map(255) and a masked oxygenation map (260). In an embodiment, any or allof the three maps are coregistered with, and overlaid on an ultrasoundimage (step 265). A display can be provided for display of one or moreof the displayable images displayed in steps 270, 275, 280, 285, 290 and295. In an embodiment, a group of two or more of the images may bedisplayed on the same screen, and may be commonly scaled and sized. Inan embodiment, the group of all six images may be displayed on the samescreen, and may be commonly scaled and sized.

In an embodiment, the system performing processing on the optoacousticdata, and/or the system displaying the optoacoustic output—which may,but need not be the same as the system acquiring the sinogram—wouldprovide the operator the ability to vary parameters used in processing,when processing or viewing optoacoustic images. In an embodiment, thesystem performing processing on the optoacoustic data, and/or the systemdisplaying the optoacoustic output would provide the operator theability to switch on and off, and potentially vary the order of, theprocessing steps used to process the optoacoustic images.

Preprocess (220)

Turning to FIG. 3, an overview of an exemplary sinogram preprocessing isshown. After acquisition of sinogram data (step 205, 210), that data ispreprocessed (step 220, FIG. 2) in one or more separate manners toreduce or compensate for undesired data in the sinogram, including,without limitation, artifacts of the device itself, artifacts of thedevice-subject interaction, and external sources of unwantedinformation. In an embodiment, preprocessing may consist of one or moreof the following steps: detecting bad transducers (step 305), commonmode stripe filtering (step 310), band pass filtering and/or applying ofa probe transfer function (step 315), normalization of the dynamic range(step 320), normalization for energy (step 325), selective channelsensitivity (step 330), interframe persistent artifact removal (step335) and software time gain compensation step (340). One or moreadditional preprocessing steps may also be used to reduce or compensatefor undesired data in the sinogram. Notably, the steps identified inFIG. 3 do not need to be performed in the order presented, and may beperformed in any order. Moreover, not all of the steps presented in FIG.3 are required for any implementation of an exemplary system, rather,preprocessing consists of the use of any one or more steps to reduce orcompensate for undesired data in the sinogram.

Preprocess (220)—Detect Bad Transducer (305)

One potential source of malady in the sinogram is a transducer thatfails to accurately reflect the optoacoustic return signal incidentthereon during the sampling process. The failure may be temporary, ormay be permanent. Moreover, the failure may be partial, such as wherethe sampled data reflecting too high or too low a signal, or reflectingnoise, or the failure may be complete, such as where the sampled dataare all zeros or nominal values. A bad transducer could also presentinconsistent or flakey output, even within a single sinogram. Badtransducer channels may also result, for example, from poor contact withthe tissue beneath one or more transducer elements.

In an embodiment, when a consistently bad transducer is identified, itsidentity is noted, and thereafter the data provided from that transducermay be ignored, replaced or separately pre-processed. For example, in anembodiment, to compensate for the misbehavior of a transducer, apre-processor is run to remove the transducer's abnormal responsecharacteristics. In another embodiment, to compensate for themisbehavior of a transducer, the transducer's data is replaced with anaverage of the data from the two adjacent channels.

In an embodiment, sinogram data is analyzed for the presence of badchannels. A bad channel may be detected by the fact that the sinogramhas a “skin” signal—that is an optoacoustic response signal reflectedfrom at or near the surface of the volume—that is significantly weakerthan the average across the other channels. A weaker skin signal mayresult from a bad acoustic contact right above the channel or someproblems, e.g., with electronics that significantly reduced the gain ofthat channel. When a channel exhibits this behavior, it may beidentified as “bad” and, in an embodiment, the data in that channel iszeroed out following the processing with a stripe filter (discussedbelow) to avoid artifacts.

In an illustrative embodiment, the algorithm below may be used foridentifying bad data channels and zeroing that part of data, therebyavoiding inaccurate image artifacts.

In this illustrative embodiment, an algorithm assumes that a strongoptoacoustic skin signals is supposed to be received by each transducer.The strong optoacoustic skin signal is expected to dominate over noiseand are expected to be close in magnitude from channel to channel.

The illustrative algorithm is described as follows: each connected datachannel is analyzed and labeled “bad” if the average of a group ofseveral consecutive samples of absolute channel data (containing theoptoacoustic signal from the skin) is very small and considered to be astatistical outlier when compared across all the connected channels. Theoutlier determination is based on the weighted standard deviation acrossall the channels.

An illustrative algorithm may be executed as follows:

-   -   a. Absolute values of the signals are calculated.    -   b. Average values of the first several samples in absolute        signals are calculated.    -   c. Small outliers of the average values are identified using the        average across all the connected channels minus weighted        standard deviation as a threshold.    -   d. Identified outliers are labeled as bad channels.

Pseudo-code in the Appendix will provide a guide for a person ofordinary skill in the art in implementing illustrative algorithmsdiscussed herein. The algorithm presented is merely an example of oneway to remove bad channels that can adversely affect the latercalculations and operations made upon the optoacoustic data. In view ofthe foregoing, it will be apparent to a person of skill in the art, andwithin the scope of this disclosure, that other methods can be used fordetecting bad channels, including, without limitation, methods that usean autocorrelation between channels, or between sets of channels.

Preprocess (220)—Common Mode Stripe Filter (310)

Other potential sources of unwanted information in the sinogram mayappear in the form of noise or other unwanted signal that affects allchannels simultaneously. There may be a variety of causes of this kindof noise or unwanted signal, including, for example, externalinterference or probe characteristics. Regardless of the cause, however,the noise or unwanted signal may be removed or mitigated. When thesinogram is oriented with channels corresponding to columns, and samplesaccording to rows, this type of filter removes horizontal stripes fromthe sinogram. In an embodiment, horizontal stripes may be removed usinga method based on the 2-Dimensional Discrete Wavelet Transform (2D-DWT).In an embodiment, horizontal stripes may be removed using a method basedon a frequency domain filter (e.g., a 1-dimensional or 2-dimensionalfrequency domain filter) or FIR filter. In an embodiment, an averageacross a row or other set of data is subtracted from each sample in thatrow or set of data.

In an illustrative embodiment, the algorithm below may be used forremoving horizontal stripes from a sinogram. In an embodiment, theillustrative algorithm may be executed as follows:

-   -   a. Precompute the sizes of the wavelet coefficients for the        horizontal coefficients at each subband level.    -   b. Precompute the even-symmetric zero-phase transfer function of        the 1-Dimensional (1D) frequency domain stripe filter for each        wavelet subband.    -   c. Compute a 2D wavelet transform using the highpass and lowpass        wavelet coefficients, which may be defined by the input        parameters, and by applying forward wavelet decomposition for        some number of levels.    -   d. With the vertical coefficients from each subband level, apply        the 1D transfer function filter to each line along the vertical        direction, where the 1D transfer function smoothly suppresses        low frequencies for each of the lines.    -   e. Take the inverse wavelet transform by applying wavelet        reconstruction to the modified wavelet coefficients

Pseudo-code in the Appendix will provide a guide for a person ofordinary skill in the art in implementing this illustrative algorithm.The algorithm presented is merely an example of one way to implement astripe filter to remove data that can adversely affect the latercalculations and operations made upon the optoacoustic data. In anembodiment, common mode stripe filtering can be performed by usingprincipal component analysis on the channels of the sinogram to removeinterference that is common to each channel. In view of the foregoing,it will be apparent to a person of skill in the art, and within thescope of this disclosure, that other methods can be used for removingthis type of errant data.

As a wave travels along the surface of the tissue, illustratively, thewave's crest may meet each element of the transducer in sequence;accordingly, such a wave may produce diagonal artifacts in the sinogramwhen measurement is acquired using a linear-array probe. In anembodiment, the stripe filter may be used to remove these and other suchdiagonal artifacts. In an embodiment, to remove such diagonal artifacts,each channel of the sinogram may be shifted based on the perceivedtravelling speed of the surface wave prior to application of the stripefilter and then un-shifted after the stripe filter has been applied. Inan embodiment, diagonal stripes may be removed using a 2D band-rejectstripe filter.

Preprocess (220)—Band Pass Filter and Probe Transfer Function (315)

The acquired channels of optoacoustic return signal data captured by thetransducers and stored in a sinogram comprise a sampling of the data thetransducers detect (during the sampling period). As discussed above, thesinogram-resident samples are acquired in the time domain. As alsodiscussed below, the optoacoustic return signal transducer may have awider band than a traditional ultrasound transducer. Thus, in anembodiment, an optoacoustic return signal transducer may have a bandwidth from 10 Khz or lower, to as high as 20 Mhz or more. In anillustrative embodiment, an optoacoustic return signal transducer mayhave a band width from about 50 Khz to 20 Mhz.

Selected portions of the optoacoustic return signal have been moresuitable for use in image reconstruction. Thus, in an embodiment,portions of the optoacoustic return signal are eliminated withoutmaterially detracting from the resulting optoacoustic image. In anembodiment, a one dimensional FFT (Fast Fourier Transform) band passfilter may be used to reduce or remove the high and low frequencycomponents without material detraction from the resulting optoacousticimage. Thus, in an illustrative embodiment, a one dimensional FFT bandpass filter can be employed that, on the low frequency side, providessubstantially complete attenuation at less than 10 Khz, while on thehigh frequency side, provides substantially complete attenuation after12 Mhz. In an embodiment, a one dimensional FFT band pass filter can beemployed that, on the low frequency side, starts to roll off at 50 Khz,while on the high frequency side, starts to roll of at 6 Mhz. In anembodiment, the roll off rate is steeper for the low frequency side thanthe high frequency side. Thus, in an illustrative embodiment, a onedimensional FFT band pass filter can be employed that, on the lowfrequency side, starts to roll off (downwardly) at 50 Khz, and providessubstantially complete attenuation at less than 10 Khz, while on thehigh frequency side, starts to roll of at 6 Mhz, and providessubstantially complete attenuation after 12 Mhz.

In addition to filtering frequency portions of the optoacoustic returnsignal that have no material effect on the resulting optoacoustic image,in an illustrative embodiment, an algorithm may provide an approximationof the transfer function of the probe and the electronics, i.e., afunction that substantially approximates the system's transfer function.As used in this section, the system's transfer function (i.e., thefunction that substantially approximates the system's transfer function)is a transfer function that reflects at least some of the system's ownresponse characteristics, such as the probe geometry, the way the probeitself affects a light event or the resulting optoacoustic return signalat varying frequencies, including changes in, e.g., attenuation, delay,spatial response, noise or other aspects of the signal. In anembodiment, spatial frequency response characteristics of the tissueand/or the coupling medium may also affect the system's own responsecharacteristics. The frequency domain response characteristics, orimpulse response characteristics of the system electronics also may beincluded in the system response. Examples of the kind of responsecharacteristics that could be introduced by a system response mayinclude: filtration of frequencies such that, e.g., sound at 1 Mhz comesthrough louder than sound at 100 Khz; delay such that, e.g., sound at 1Mhz comes through sooner than sound at 100 Khz; and/or spatial effects,such that, e.g., a sound arriving at the transducer from a location 45degrees from normal with respect to the transducer sounds different thanit would if it arrived from a direction normal to the transducer.

In an illustrative embodiment, an overall system filter (i.e., a filterto compensate for, among other things, the system transfer function) mayformed by steps including deconvolution of the acousto-electric impulseresponse, bandpass filtering, and an additional arbitrary transferfunction to support filtration of other factors. The sinogram data canthen be processed using the system filter function.

In this illustrative embodiment, the system's complex transfer functionis formed out of three parts, which are later multiplied together. Thefirst part is the frequency domain representation for deconvolution ofacousto-electric impulse response, which may be determined using Wienerdeconvolution with a regularization parameter that pertains to thenoise-to-signal power spectral ratio. The second part of the transferfunction is the bandpass filter, which is designed with a raised cosineapodization function, using provided information on the band pass/stopregions. The third part of the transfer function is an optionalarbitrary frequency response. The system filter only needs to berecalculated if one of its parameters changes. Otherwise the filter maybe determined, stored, and loaded from the storage as needed. In short,the sinogram data is conditioned and transformed into the frequencydomain, where it is multiplied by the system's filter function before itis transformed back into the time domain.

An illustrative algorithm for making the system filter may be describedas follows: If none of the parameters were modified since the last run,the system's transfer function is the previously calculated inputsystem's transfer function. Otherwise the system filter may becalculated according to the following steps. In step one, thedeconvolution Wiener filter is formed. (A Wiener deconvolution filter asfollows may be used:

${G(f)} = \frac{H^{*}(f)}{{{H(f)}}^{2} + {\alpha(f)}}$where f—frequency (Hz), G—transfer function of the filter, H—system'sfrequency response, α—noise-to-signal spectral power density ratio.) Inthe step two, the bandpass filter is calculated using a raised cosineapodization function and input band pass/stop frequency parameters. Ifspecified by the parameters, the bandpass filter may be unity (aconstant value of 1), and hence, no bandpass filtering is applied. As alast step, those two complex transfer functions are multiplied togetherwith another defined arbitrary transfer function (optional) to get theoutput system filter function. One purpose for multiplying the twocomplex transfer functions with another defined arbitrary transferfunction is to allow frequency domain filtering that is not readilysusceptible to filtering using the other two methods.

An illustrative algorithm for processing data according to the systemfilter function may be described (for a single channel of data) asfollows: The input data is zero-padded (or symmetrically padded) todouble the length and is transformed to the frequency domain via theFast Fourier Transform (FFT), complex-multiplied by the system'stransfer function, and then the Inverse Fast Fourier Transform (IFFT)applied, to return the data to the time domain. Once returned to thetime domain, the padding is removed.

Pseudo-code in the Appendix will provide a guide for a person ofordinary skill in the art in implementing this illustrative algorithm.

In an embodiment, overall system compensation may be performed and usedto mitigate, eliminate or enhance portions of a sinogram. In anembodiment, overall system compensation may be used to account forsituations that are not limited to ideal lab situations or factors basedsolely on the probe and the electronics; rather the characteristics ofthe sinogram may be affected by the physiology and characteristics of atypical subject and embody non-ideal situations that do not strictlyoccur in the lab. Difficult-to-model interactions may occur inreal-world situations that differentiate in-vivo optoacousticmeasurements from models. These can include interactions involvinggeometry of a probe that is part of the system; the manner in which theprobe affects a light event caused by the system; the way in which theprobe affects attenuation, delay, spatial response, noise or otheraspects of an optoacoustic return signal; spatial frequency responsecharacteristics of a tissue being imaged, and a coupling medium used inconnection with recording the sinogram. In many cases these situationsmay also be anticipated and be replicable, though they may result fromcombination of factors that would have be unlikely to foresee even whenusing simulated environments, e.g., phantoms. Accordingly, in anembodiment, overall system compensation or calibration can encompassaccounting for these factors by performing analysis based on a multitudeof acquired datasets; the process to determine the overall systemcompensation can be based on empirically tuning the overall systemcompensation to meet a performance objective. In an embodiment, tuningcan be based on collecting a multitude of datasets and performing astatistical regression analysis, the objective of the statisticalregression may involve optimizing a cost function, or using manualoperator adjustment; performing an offline computation to determineparameters for computation; fitting parameters to match the objective;determining spatial or temporal weights for a table, the table used inreconstruction to account for factors including geometry; or using thestatistical or manual analysis to determine the weights of an optimalfilter. In an embodiment, the statistical analysis may involve usingspecialized computer software for performing the analysis. In anembodiment, the statistical analysis may yield different optimal tuningparameters for different types of tissue or for subjects of differentphysiology. A method for tuning may account for these factors. In anembodiment, a method for tuning may have, as its objective, the yield ofoptimal results, or the enhancement of features for different tissues.For example, enhancement or optimal results may be sought for dense orfatty breast tissue or other known types of tissue as may bedifferentiable; likewise, enhancement or optimal results may be soughtfor any types of characteristics, including, without limitation: thickor thin layers of skin; the mechanism by which light is absorbedseparately based on the tone of skin; the emphasis of a tumor or lesion,including where the tumor or lesion has different frequencycharacteristics than the background tissue; the differences between acellular or non-cellular fibroadenoma (or other such determinablecondition) and sets of parameters to make this more apparentoptoacoustically; the differences between classes of malignant andbenign lesions and other indeterminate structures yielding anoptoacoustic signature (e.g. lymph nodes, fat necrosis) and a system ormethod for discriminating such; features of different scales or sizes;tuning parameters such as packet wavelet coefficients or vector supportcoefficients involving feature detection classification; or adjustableparameters in a deconvolution process. The method for tuning may includeacquiring data under strictly controlled measurement conditionsaccording to a measurement procedure, wherein the probe is manipulatedto according to specific or specialized motions (e.g. sweeping orfanning) and specific portions of tissue are captured (e.g. parenchyma).In an embodiment, the method for optoacoustic tuning may comprise:collection of measurements; statistical or manual analysis involvingoptimizing an objective; adjusting parameters to obtain the desiredsystem compensation; and applying the compensation to the sinogram thusaffecting the resulting diagnostic overlay. In an embodiment, thecompensation may be performed separately for two or more wavelengths. Inan embodiment, the tuning analysis may be used to generate a set ofrules that can be applied to an optoacoustic image or other system datato develop a prognosis or histology. The rules so generated may beapplied by an operator, by the system, or by another system, and onceapplied, may provide a report of the prognosis or histology. In anembodiment, multiple sets of pre-tuned parameters may be user-adjustableor enable-able by a user interface, which user interface may include aset of pre-tuned parameters.

Preprocess (220)—Normalization of Dynamic Range (320)

As discussed below, time gain compensation may be applied in hardware toachieve higher dynamic range and/or improve the signal to noise ratio(SNR) for a given depth or distance. Hardware applied time gaincompensation may improve the overall dynamic range of the optoacousticreturn signal. Analog hardware applied time gain compensation mayincrease the precision of the data captured by the analog-to-digitalconversion device by amplifying low magnitude signals from deep tissuethat would otherwise not effectively use the full bitwise representationof the data. In addition, analog hardware applied time gain compensationmay improve the signal-to-noise ratio by bringing weak signals at depthabove an analog noise limit in the pathway between the hardware TGCamplifier and the analog-to-digital conversion device. In an embodiment,time gain compensation may compensate for the attenuation that occurs tothe light as it transmits from a surface of a volume of e.g., tissue toareas within the volume of tissue, and/or for attenuation to theoptoacoustic return signal as it transmits through the volume of tissue.In an embodiment, the image reconstruction algorithms utilized presume,however, that there has been no change in gain, e.g., amplifying lateror deeper signals. Accordingly, in an embodiment, to normalize the data,the hardware time gain compensation is mathematically reversed, thusremoving its impact from the image calculation.

In an embodiment, the sampled data is a relatively modest sized integer,such as a 14 bit integer, which e.g., can represent values from 0 to16,383. In an embodiment, the data in the sinogram is converted frominteger to floating point prior to the processing discussed in thissection; conversion from integer to floating point may be performed toincrease accuracy and expand the dynamic range of the calculations.Generally, care should be exercised to prevent the loss of dynamic rangewhen reversing the hardware time gain compensation. In an embodiment,the normalization of dynamic range filters the sinogram to reflectsubstantially flat gain without loss of dynamic range. It permits eachsample in the sinogram to sum its proper contribution when used inconnection with forming the resulting optoacoustic image.

In an embodiment, to renormalize the dynamic range, the time dependenthardware TGC curves may be factored out of each channel. In anembodiment, hardware TGC curves may be stored as a set of data pointsthat are linearly interpolated by the system firmware and sent to thehardware TGC amplifier. A TGC curve may be computed from stored datapoints.

An illustrative algorithm for renormalizing the dynamic range of asinogram follows: generate the TGC curve, send the TGC curve to thehardware TGC amplifier, if necessary, linearly interpolate the TGC curveto create a piecewise linear curve equal in length to the number ofsamples, map the computed curve from a numeric representation as may berequired by the hardware to the amplifier gain, compute the reciprocalof the gain curve, and finally, multiply the corresponding samples inthe reciprocal curve by the samples of each channel and store the resultas output.

Pseudo-code in the Appendix will provide a guide for a person ofordinary skill in the art in implementing illustrative this algorithm.

Preprocess (220)—Energy Normalization (325)

In an embodiment, the sinograms contain optoacoustic return signal datacorrespond to a single light event such as the firing of a laser. Inuse, the system 100 may produce a plurality of sinograms, eachcorresponding to a separate light event. For example, in an embodiment,a single light source can be used repetitively, with the systemgenerating a separate sinogram to capture optoacoustic return signaldata from each. In another embodiment, two or more light sources can beused to generate discrete light events, such as, for example, byinterleaving them so that one is used and then the other, with thesystem generating a separate sinogram to capture optoacoustic returnsignal data from each. In an illustrative embodiment, an ND:YAG laserand an Alexandrite laser are used in an interleaved manner, with onecausing a light event and then the other. In each of the foregoingmultiple light event situations, the energy of one light event maydeviate from the total energy of another. Deviation from one light eventto another may, or may not be intended, and may be the result ofexternal influences or system design or a combination of factors. Forexample, most lasers fluctuate in energy, at least to some degree andoften to a large degree, each time they are used in the manner describedin more detail below.

Regardless of the cause, in an embodiment, it may be desirable to reduceor eliminate the shot-to-shot variance. Such shot-to-shot variance can,for example, create problems in using the sinogram data to produceconsistent images. Moreover, when images are shown in sequence,shot-to-shot variance can cause flicker, not unlike that seen in an oldtime movie. As a result, shot-to-shot variance can inhibit or preventadequate review of image sequences, or inhibit or prevent adequateinterpretation of images created by different lights in two separatelight events such as of the image pairs created using an ND:YAG laserand an Alexandrite laser as discussed.

In an embodiment, energy normalization can be accomplished by dividingeach sample by a value proportional to a measured energy of the lightevent so that each sample in the sinogram would thereafter represent anormalized value. In an embodiment, energy normalization can be used inconjunction with a calibration procedure, for example, by setting theinitial energy of laser output to a specified level and normalizing theenergy deviation against that level.

Pseudo-code in the Appendix will provide a guide for a person ofordinary skill in the art in implementing this illustrative algorithm.

Preprocess (220)—Selective Channel Sensitivity (330)

The sinogram data may contain variations that are related to theperformance of specific components of the system. Such variations cancause inaccuracy and/or unwanted or undesired results in imagesreconstructed therefrom. In an embodiment, information is storedconcerning such variations and the information is used to process thesinogram and remove variations that are related to the performance ofspecific components of the system such as a channel-to-channelvariation. In an embodiment, the channel sensitivity process may beperformed in a manner to account for variations in signal strengthresulting from signal variation related to contact, the coupling mediumand other such issues (e.g., performed adaptively or dynamically). In anembodiment, dynamic compensation may be performed by using channels inclose proximity to each other, which may be presumed to have similarcontent, to determine a dynamic compensation factor of each channel. Inan embodiment, the sinogram is filtered prior to performing dynamicselective channel sensitivity.

In an illustrative embodiment, an optoacoustic device comprises a probehaving 128 or 256 transducer elements. Each of the transducer elementsare electrically connected to one amplifier. Each of the amplifiers mayhandle, e.g., 8 individual transducers, thus, a total of 7 or 8amplifiers may be required in this illustrative embodiment. A DAP board(i.e., data acquisition processor board) may contain 8 such amplifiers,and thus be used to acquire data from all 128 or 256 transducerelements. Variations may occur between the response of the severaltransducer elements. Generally, for example, each amplifier has a singlegain control that may affect the gain on all 8 transducers it ishandling. Accordingly, if one or more of the transducer elementsresponds differently, e.g., more quietly, than the other transducerelements connected to the same amplifier, it cannot be compensated forusing the gain control. Similarly, variations may occur between theresponse of the several amplifiers, leading to variation in what wouldotherwise be identical transducer element responses. Variations in mayalso occur due to the amount of pressure applied to the probe, includingdifferent amounts of pressure being applied to different regions orelements on the probe. Variation may additionally occur due to thequality or amount of skin or surface contact with the probe, or theamount of coupling medium used. Surface features, such as roughness,physiological structures near the surface, or focusing aberrations mayalso produce variations in the signals received on a per-channel basis.In an embodiment, variations can be detected using an automatic methodor a fixed method that is determined by measuring and calibrating aparticular transducer.

In an embodiment, calibration data for a probe indicative of therelative or absolute performance of the transducer elements may bemaintained. Similarly, calibration data for a DAP board indicative ofthe relative or absolute performance of the amplifiers may bemaintained. Such calibration data may be acquired at the factory atmanufacture time by using known inputs or tests, or alternatively, maybe acquired later, e.g., in the field, using calibration equipment. A“dummy” probe that is calibrated to transmit specific output signals maybe used to help determine calibration information for the amplifiers. Aknown phantom may be used to help determine calibration information forthe transducer elements. In an embodiment, the probe holder contains aknown acoustic or optoacoustic response that can be used to runcalibration tests, or to confirm that the system is functioning in anconsistent manner.

In an embodiment, a test sample is provided that is expected to producea given output X from each transducer element. When the test sample istested, the response from most channels is indeed X, but from severalchannels is 0.9X, and from one channel 0.85X. In an embodiment, thesinogram column corresponding to the 0.9X channels are enlarged by afactor of 1/0.9, while the sinogram column corresponding to the 0.85Xchannel is enlarged by a factor of 1/0.85. Where a channel responds with1.1X it can similarly be multiplied by a factor of 1/1.1.

The foregoing presumes that any channels that differ from the expectedoutput will do so in a linear manner. Where this presumption isinsufficient to accommodate the actual deviation, a more complextransfer function can be used to compensate for the actual sensitivityof a channel.

Preprocess (220)—Interframe Persistent Artifact Removal (335)

For the purpose of the following discussion, the optoacoustic returnsignal data can be thought of to include three components: the desiredcoupled response; the undesired coupled response; and noise. Interframepersistent artifact as used in this section refers to the undesiredcoupled response, not to other noise. Unless compensated for, interframepersistent artifacts may be present in images created from anoptoacoustic return signal created using a handheld probe that providesboth the light and the transducer elements. The interframe persistentartifact is generally not the same from one tissue or volume to another,however, a sub-component of the interframe persistent artifact mayremain the same between all data collected using a given set ofhardware, or even a given probe. More generally, while two similarphantoms may create similar interframe persistent artifacts, tissuecreates different interframe persistent artifacts than a phantom, andone person's tissue creates different interframe persistent artifactsfrom another person's tissue. Moreover, generally, the amount ofinterframe persistent artifacts present in most common phantoms may belower than, or different than, the interframe persistent artifactspresent in most tissue.

It has been found that interframe persistent artifacts are relativelystable for a given individual, and more so, when collecting data aroundnearby locations. Thus, for example, the shot-to-shot variance ininterframe persistent artifacts are relatively low shots of a singleindividual, but relatively much higher for shots of differentindividuals. The interframe persistent artifacts may also remainrelatively stable when similar amounts of coupling medium are used, andwhere the pressure applied to the probe, and thus the probe contact,remains consistent. A method of mitigating interframe persistentartifacts from sinogram data comprises the removal of common data fromseparate, spatially distinct frames. In an embodiment, common data canbe removed from separate, spatially distinct frames using singular valuedecomposition (SVD) algebra, principal component analysis (PCA), orother similar methods. In an embodiment, common data can be removed fromseparate, spatially distinct frames using a principal component removalalgorithm. Typically, the singular value decomposition and principalcomponent removal will require a sufficient number of independent frameswhere the interframe persistent artifact remains substantially constantand the collected data is changing and uncorrelated at a given sample orpixel. In an embodiment, more than 3 uncorrelated frames, and preferablymore than 20 to 30 frames form the data set for analysis to remove theinterframe persistent artifacts. In an embodiment, at least about 50frames are analyzed in connection with an algorithm to remove interframepersistent artifacts.

In an embodiment, Interframe persistent artifact removal is performed ona per-light-source basis, meaning that where, for example, both YAG andAlexandrite lasers are used for different frames, YAG frames only areanalyzed for Interframe persistent artifact removal from the YAG frames,and Alexandrite frames only are analyzed for Interframe persistentartifact removal from the Alexandrite frames. It should be noted thatthe expression per-light source is substantially directed at thewavelengths for the light source. Generally, lasers do not operate at asingle wavelength, but rather, lasers produce light in a narrow range ofwavelengths, often characterized by a dominant wavelength, whichwavelength is used as a reference to for that laser. Thus, for example,a Nd:YAG laser output is often tuned to, and described as a 1,064 nmwavelength, not because the laser output is solely and precisely at thatwavelength, but rather, because that is its predominant wavelength oflight output. Similarly, an Alexandrite laser, which can be tuned to avariety of wavelengths from about 700 to 820 nm, and as used herein isgenerally tuned to, and often described as a 757 nm wavelength, is notintended to describe a precise wavelength, but rather a predominantwavelength in a narrow-band output of such a laser. Accordingly, as theterm “per-light-source basis” is used above, if a tunable (rather thanpre-tuned) laser were used, it would be considered one light-source forall frames created at substantially the same wavelength setting.

In an embodiment, where the total light energy for each frame is knownor can be estimated, it may be advantageous to perform Interframepersistent artifact removal on frames having similar total light energy.Thus for example, in an embodiment, Interframe persistent artifactremoval may be performed on a per-light-source basis for frames havingmore than average light energy, separately from the frames having lessthan average light energy. In an embodiment, the frames for a givenlight-source are divided into a plurality of groupings based on thetotal light energy for the frame, and Interframe persistent artifactremoval is performed on each of the plurality of groupings. In anembodiment, the plurality of groupings is determined based on dividingthe frames equally into the desired number of groupings, i.e., ⅓ in thefirst group, ⅓ in the second group, ⅓ in a third group. In anembodiment, the total light energy for the frames can be analyzed andthe frames divided statistically, with those falling within astatistical grouping being analyzed together. For example, frames havingtotal light energy of within one standard deviation of the mean may fallinto a first category, frames more than one standard deviation above themean fall into a second category and the remainder fall into a thirdcategory.

In an embodiment, an estimate of the interframe persistent artifacts iscreated from an average for each sample, for each channel, across arelatively large set of sinograms, e.g., 50 or more. In an embodiment,an estimate of the interframe persistent artifacts for each wavelengthis created from an average for each sample, for each channel, for agiven wavelength, across a relatively large set of sinograms, e.g., 50or more. In an embodiment, the sinograms forming the set comprising theestimate set are spatially distinct from each other—i.e., captured froma differing regions of tissue. In an embodiment, each sinogram being acandidate for addition to the set of sinograms used in forming theestimate is rejected if it is not spatially distinct from the previoussinogram. In an embodiment, a test is run on a frame to ensure that itis spatially distinct from the previously used frame before it ismathematically embodied in the estimate. In an embodiment, the estimateis updated with each subsequent frame, or each new frame for the givenwavelength. In an embodiment, the estimate is updated with apredetermined number of new frames (or new frames for the wavelength),and then remains consistent for the reading, or for some longer period.In an embodiment, the estimate is updated with each subsequent frame, oreach new (spatially distinct) frame for the given wavelength. In anembodiment, the estimate is updated with a predetermined number of new(spatially distinct) frames (or new (spatially distinct) frames for thewavelength), and then remains consistent for the reading, or for somelonger period.

In an embodiment, the estimate is updated using a moving window offrames representing a fixed number of the most recent frames taken in areading. In an embodiment, an estimate for a specific individual isassociated with that individual and retained for future use with theindividual. In an embodiment, as estimate for a specific individualcreated with a given probe is associated with both the individual andthe probe, and retained for future use with the same individual andprobe.

In an embodiment, the detection of motion of the probe is used todiscriminate and ensure that the frames collected for estimating theinterframe persistent noise are independent or not correlated; i.e.,when zero or little motion is occurring, the frames are correlated. Inan embodiment and automatic motion detection algorithm may be performedon a sinogram, or on a reconstructed image, to determine if motion isoccurring. In an embodiment, phase correlation may be used on two ormore reconstructed images to determine the extent of motion that hasoccurred there-between. In an embodiment, a frequency-domain filter maybe applied to two or more sinograms or images, and the correlation ordifference between frames, may be used to determine if substantialmotion has occurred between the frames; the more similar the frames, theless motion that has occurred. In an embodiment, low frequencies may befiltered out prior to motion detection since dominant interframepersistent artifacts are found in lower frequencies, whereas manystructures in the tissue, such as blood vessels and tissue boundariescorrespond to higher frequencies. In an embodiment, the interframepersistent noise estimate may be filtered in the frequency domain (or inanother domain) to prevent structures such as the skin layer—whichremain constant but is not considered unwanted—from inadvertent removal.

In an embodiment, where a “live” display is provided, an estimate can beformed using a plurality of prior frames. In an embodiment, where a“live” display is provided, an estimate can be formed using a pluralityof prior spatially distinct frames. In an embodiment, where a “live”display is provided and the system comprises a satisfactory frame rate,the estimate can comprise past frames and future frames, provided thatthe display is delayed in time to permit the use of such frames. Thus,for example, where the frame rate for a given laser is, e.g., 5 framesper second, and the display is about one second behind real time, it maybe possible to use four or five “future” frames to estimate theinterframe persistent artifacts in the current frame. It will beapparent to one of skill in the art that “future” frame data can beincorporated into an estimate where the display is provided in anoffline (e.g., non-live) playback system.

In an embodiment where a display output is provided after a reading iscomplete, all of the spatially distinct frames (or all of the spatiallydistinct frames of a give wavelength) can be used in creating apost-reading estimate of interframe persistent artifacts, and thenentire reading can be reconstructed and output with the post-readingestimate of interframe persistent artifacts eliminated from thesinograms prior to their reconstruction.

In an embodiment, interframe persistent artifact estimation and removalis performed post-reconstruction, on the reconstructed image, or on anintermediate image formed after reconstruction, rather than performingthis step on the sinogram data. In an embodiment, interframe persistentartifact estimation and removal is performed post-reconstruction on thereal, imaginary or both components of complex images reconstructed fromcomplex sinograms; complex images and sinograms are discussed in moredetail below.

In an embodiment, the estimate of interframe persistent artifacts isused as a basis to modify sinograms prior to image reconstruction. In anembodiment, the estimate of interframe persistent artifacts is used tosubtract artifacts out of the sinogram prior to image reconstruction.

In an embodiment, an estimate for the interframe persistent artifact canbe computed by using the first principal component of the independentanalysis frames. In an embodiment, independent component analysis can beused to estimate the interframe persistent artifact from the independentanalysis frames in a similar fashion.

The following processing steps are illustrative of an embodiment of theInterframe persistent artifact removal algorithm.

-   -   a. compute the interframe persistent artifact estimate;    -   b. compute the scalar product “P” of the interframe persistent        artifact estimate on the input data containing the artifact;    -   c. from each element of the input, subtract the projection of        the interframe persistent artifact on the input from the input,        by subtracting each corresponding element in the interframe        persistent artifact estimate multiplied by P from the input and        storing the result in the output.

Pseudo-code in the Appendix will provide a guide for a person ofordinary skill in the art in implementing this illustrative algorithm.

Preprocess (220)—Software Time Gain Compensation (340)

After a light event in tissue produces sound via an optoacoustic effect,the sound attenuates as it travels through the surrounding tissue. Asthe acoustic wave propagates through the tissue, its energy is absorbedby the tissue. In general, the further the sound has traveled, the moreof its energy will have been lost, i.e., into the tissue or otherpropagation medium. In addition, the longer it takes sound to reach thetransducer, the father it has traveled (assuming a constant speed ofsound). For example, in the illustrative embodiment above, more than2,000 samples are taken at a frequency of 31.25 Mhz, thus sampling forabout 65 microseconds of time, which corresponds to a distance ofsomewhere around 100 millimeters, depending on the speed of sound in theparticular tissue. Thus, later samples in the sinogram have greatlyattenuated high frequencies as compared to the earlier samples, whichhave less attenuated high frequencies. The tissue structures andmaterial constituents of the propagating medium (including, e.g., theacoustic lens and/or transducers), as well as physical boundaries orlayers found within the medium may play a role in the attenuation, andthus the received energy of the optoacoustic return signal. In anembodiment, attenuation in an homogenous medium can be modeled as anexponential decay curve (e.g., as ideal), but the degree to which thisholds true depends on the particular tissue or other volume beingimaged. In an embodiment, compensation is performed on a per channelbasis. In an embodiment, the samples are amplified by a factor relatedto the time they were received.

An illustrative embodiment of the software time gain compensationalgorithm is provided below:

-   -   a. Compute a 1D compensation curve based on a function of time        corresponding to the sample number in the measured channel data.        (In an embodiment, the 1D compensation curve may be based on an        exponential decay curve with nominal acoustic attenuation        corresponding to the one-way propagation of the acoustic wave        from the optoacoustic source to the transducer.)    -   b. For each channel in the sinogram        -   i. Multiply each sample in the input sinogram by the            corresponding compensation value in the 1D compensation            curve        -   ii. Place the resultant multiplied value into the output            sinogram at the corresponding sample and channel

Pseudo-code in the Appendix will provide a guide for a person ofordinary skill in the art in implementing this illustrative algorithm.

Preprocess (220)—Sub-Band Acoustic Compensation (345)

Typically, as between the higher and lower frequencies informationcontained in the optoacoustic return signal, the higher frequencies maycorrespond to smaller sources and boundaries, and the lower frequenciesmay correspond to larger sized objects. During acoustic wave propagationin tissue, however, higher frequencies typically attenuate more andlower frequencies typically attenuate less. In other words, higherfrequency acoustic waves are more attenuated than lower frequencyacoustic waves traveling the same distance, and thus, received at (ornear) the same time. This difference in attenuation can createdistortion in a reconstructed optoacoustic image. Moreover, the higherfrequency acoustic waves travel in tissue at a somewhat differing ratethan lower frequency acoustic waves counterparts. Accordingly, toprovide more accurately reconstructable data (e.g., sinogram),compensation may be made for time on a per frequency basis, and foramplitude on a per time basis.

To perform compensation for frequency dependent attenuation, the higherfrequency information may be amplified, or may be amplified more thanlower frequency information. In an embodiment, such amplification may beperformed by applying compensation separately to sub-bands of the data,each sub-band corresponding to a filtered range of frequencies from thedata. Applying the compensation to sub-bands rather than individualfrequency components reduces computational load, and thus the need forcomputational resources. In an embodiment, in each sub-band, oldersamples (i.e., samples received later in time) are amplified more thannewer samples. Compensation values can be estimated for tissuegenerally, or for specific tissue of interest, by measuring attenuationand speed of sound in tissue samples at varying frequencies.

Thus, in an embodiment, frequency domain sub-bands are identified whichassociate sub-band compensation factors, approximately, to the frequencydependent attenuation of the signal. In an exemplary embodiment of asub-band acoustic compensation method, the compensation factorsassociated with a particular sub-band may be calculated in relation todepth and the center frequency associated with the sub-band. In anembodiment, to account for effects of depth related distortion as afunction of a particular depth, d, and center frequency, fc, thecompensation factor f(d, fc) may be calculated as f(d,fc)=exp(d*fc/1,000,000). In an embodiment, the compensation factor f(d,fc) may be calculated as f(d, fc)=exp(d*fc^g/a0), where g and a0 areparameters. In an embodiment, g equals 1.0 and a0 equals 1,000,000. Inanother embodiment, g and a0 are configurable parameters. In anembodiment, the system performing processing on the optoacoustic data,and/or the system displaying the optoacoustic output—which may, but neednot be the same as the system acquiring the sinogram—would provide theoperator the ability to vary the g and/or a0 parameters when processingor viewing optoacoustic images.

The following processing steps are an illustrative embodiment of aSub-band Acoustic Compensation (345) algorithm as implemented to processsinogram data:

-   -   a. Compute a list of frequencies corresponding to each sample in        the frequency domain.    -   b. Compute an array corresponding to the distance of an        optoacoustic source to a transducer pertaining to each sample in        the received optoacoustic signal. This may be done by        multiplying the known time delay for each sample (i.e., based        upon when it is received) with the nominal speed of sound for        the volume of tissue.    -   c. Compute a sub-band filter for each sub-band.    -   d. Create an array to store an output sinogram and initialize        each element to zero.    -   e. Compute the Fourier transform of the input sinogram for each        channel to create the frequency domain data    -   f. For each sub-band filter, for each channel,        -   i. multiply the frequency domain data by the sub-band filter        -   ii. compute the inverse Fourier transform of the result        -   iii. multiply the result element-wise by the compensation            factor for the sub-band        -   iv. accumulate the result in an output sinogram

In processing the optoacoustic return signal, information in the signalsfrom as much of the acoustic spectrum as may be detected by thetransducer may contain potentially valuable information concerning thevolume of tissue. Thus, in an embodiment, (as discussed in more detailbelow) the transducer used to receive the optoacoustic return signal issensitive to a broad band of acoustic frequencies. Because of thebroadband sensitivity, certain undesired information may also becaptured in the optoacoustic return signal, including, withoutlimitation, electronic interference, acoustic interference andmechanical interference. This undesired information is not easilyidentified in, and thus not easily filtered out of, the optoacousticreturn signal. Furthermore, frequency dependent attenuation and thefrequency dependent speed of sound are more pronounced in theoptoacoustic return signal because of the broadband nature of thetransducer sensitivity.

Because of its wideband nature, in an embodiment, the optoacousticreturn signal is subjected to one or more techniques to processdistortions across all frequencies. In an embodiment, some narrowbandsimplifications may be applied to optoacoustic data in sub-bands, wheresuch simplifications may not prove reasonable for the entire widebandoptoacoustic return signal.

Thus, in an embodiment, a Sub-band Acoustic Compensation (345) algorithmmay employ a narrowband simplification of having fixed acousticattenuation coefficient; although the simplification would not be validacross the broadband optoacoustic return signal, the algorithm can applythis simplification separately for each of the sub-bands. In anotherembodiment, a narrowband simplification can be performed by computing asmall time shift between two demodulated narrow-band signals in the timedomain; the shift being found by using phase of the inner product of thetwo complex signals rather than using a less efficient computationinvolving normalized moments of the cross-correlation function. Othernarrowband simplifications may also be employed after breaking theoptoacoustic return signal into a plurality of sub-bands, suchsimplifications reducing the computational load required for processingthe optoacoustic return signal. Following is an illustrative embodimentof a method for applying narrowband simplifications to optoacousticdata:

-   -   i) a filter bank of multiple filters can be formed to encompass        a set of sub-bands of the frequency domain so that the energy        summation (i.e., the sum of the squares) of the filters for each        frequency will have a constant value of one (i.e. “partition of        unity” property of the filter bank in the frequency domain),        and, each filter in the filter bank may conform to a        band-limited frequency range, thus, in context, the filter being        referred to as a sub-band filter;    -   ii) each sub-band filter from the filter bank is applied        separately to the optoacoustic return signal to create a        filtered representation of the optoacoustic data for each        sub-band;    -   iii) a narrow-band simplification is applied separately to each        filtered representation of the optoacoustic data to create        processed data for each sub-band;    -   iv) the processed data for each sub-band may then be        re-assembled, with the processed data for the other sub-bands,        into a final processed form, the re-assembly comprising        additively combining the contributions from all of the processed        data for each sub-band.

In an embodiment, a narrowband simplifications may be applied tooptoacoustic data by using a wavelet packet transform which usesconvolutional cascaded filter banks and downsampling operations. In anembodiment, the wavelet packet transform may be a dual-tree complexwavelet packet transform. In another an embodiment, narrowbandsimplifications may be applied in the time domain on demodulatedfiltered sub-bands where the demodulation is performed directly in thefrequency domain. Where narrowband simplifications are applied in thetime domain on demodulated filtered sub-bands, arbitrary sub-bandfilters may be used. In an embodiment, the system performing processingon the optoacoustic data, and/or the system displaying the optoacousticoutput—which may, but need not be the same as the system acquiring thesinogram—may provide the operator the ability to vary the sub-bandfilters used in the narrowband simplification, when processing orviewing optoacoustic images. In an embodiment, applying the processingmethod using a suitable narrowband simplification may reduce the amountof necessary computation.

In an illustrative embodiment, an optoacoustic data processing method isdescribed below, where the narrowband simplification is performed in thetime-domain on data demodulated in the frequency domain. In anembodiment, the FFT size of the sub-bands can be significantly smallerthan the FFT size of the full signal, by having a significantly smallerFFT size in the sub-bands, processing may be substantially faster, whileachieving substantially the same result. The following processing stepsare illustrative:

-   -   a. if appropriate, pad the signal with zero padding or symmetric        padding (optional);    -   b. convert the input signal to the frequency domain;    -   c. remove the “negative” frequencies (i.e. in the range [−fs/2,        0−]) and double the “positive” frequencies (i.e. in the range        [0+, fs/2]) to create an analytic signal in the frequency        domain;    -   d. for each sub-band, create a temporary complex-valued array        filled with zeros, with a length of at least twice the bandwidth        of the corresponding sub-band filter to store the demodulated        signals in the frequency domain. Ideally, the length of the        temporary array will be much less than the original frequency        domain signal, and thus, corresponds to a downsampling        operation;    -   e. for each sub-band, copy the values of the positive frequency        coefficients in the frequency-domain signal (within a range that        encompasses the first non-zero value of the sub-band filter to        the last non-zero value of the sub-band filter) into the        corresponding temporary array, such that a frequency domain        demodulation is performed by aligning the lowest frequency        component of the copied range with the position of the DC        frequency component in the temporary array, (note that the        temporary array will contain zeros for coefficients        corresponding to negative frequency components), the temporary        array may also be padded with additional zeros beyond the range        of copied frequency components corresponding to time domain        interpolation, which may further increase the number of samples        in the demodulated signal so the length is an optimal        power-of-two for fast Fourier transformation;    -   f. with each sub-band, apply the sub-band filter to the        corresponding temporary array by multiplying the sub-band filter        values with the temporary array values corresponding to the        aligned frequency components, and storing the result in the        temporary array as the frequency domain demodulated signal;    -   g. convert each frequency domain demodulated signal to the time        domain using the inverse fast Fourier transform (IFFT);    -   h. apply the narrowband simplification in the time domain to        each time domain demodulated signal;    -   i. covert each time-domain demodulated signal back to the        frequency domain by applying the fast Fourier transform (FFT);    -   j. modulate and sum each processed signal together in the        frequency domain and store the result as a new full-length        frequency domain signal (the modulation may be performed        implicitly by aligning the frequency domain values of the        processed signal with the positive frequency component positions        corresponding the original full-length frequency domain signal);    -   k. perform the inverse Fourier transform on the resulting        frequency domain signal;    -   l. if padding was used, remove the padding.

The time domain signal resulting from the foregoing method is the outputof this embodiment of a method of applying a narrowband simplificationto an optoacoustic data processing.

When using sub-band methods, demodulated signals may leak into othersub-bands. Such leakage may cause distortion and aliasing. Theprevention of leakage each demodulated signal into other sub-bands mayreduce distortion, aliasing and/or maintain partition-of-unity formathematical reasons. To mitigate leakage, then an additional step maybe applied for each processed demodulated sub-band in the frequencydomain prior to performing an FFT transform, namely, either:

-   -   a. apply a multiplicative windowing filter (e.g., the original        filter bank filter, or an inverse for such filter); or    -   b. apply a thresholding shaping function such that the magnitude        of each complex coefficient will not exceed the value defined by        the shaping function for each coefficient.

In an embodiment, a wavelet packet transform or a the dual-tree complexwavelet packet transform (DTCWPT) algorithm may be applied, an thus, acascaded filter bank implementation can be used rather than operatingdirectly in the frequency domain. The following steps illustrate such anembodiment:

-   -   a. apply the wavelet packet transform;    -   b. apply a narrow band simplification to time-domain sub-band;        and    -   c. then apply the inverse wavelet packet transform.

In an embodiment, a spectrogram or another method of time-frequencydomain processing can be applied to the narrow-band simplificationrather than sub-band filters. Use of a spectrogram uses time-domainbased windowing rather than sub-band filters. Regardless of whethertime-domain based windowing or sub-band filters (e.g., frequency basedwindowing) is employed, a Sub-band Acoustic Compensation (345) algorithmmay implemented to process the optoacoustic data (e.g., sinogram data)to reduce complexity and permit narrow-band simplification.

Pseudo-code in the Appendix will provide additional details of anillustrative embodiment of a Sub-band Acoustic Compensation (345)algorithm.

Preprocess (220)—Transform Operator (350)

As discussed in more detail in the reconstruction section below, for avariety of reasons, the two dimensional sinogram data as discussedherein is not susceptible to closed form reconstruction. In anembodiment, a transform operation is performed in advance of or duringreconstruction. The transform operation is used to yield more accurateresults. In an embodiment, the transform operator can be used to accountfor the geometry of the system using the propagation model of theHelmholtz equation to approximate a closed form inversion formula,thereby yielding an accurate numerical results for the case of idealreconstruction. In an embodiment, the transform operator may consist ofdiscrete operations to match or resemble mathematical operations insideof the integrand of a closed-form inversion equation, or a similarequation, for the system geometry. In an embodiment, the transformoperator may be separated from the weights of the equation because boththe transform operator and the weights may be tuned separately. In anembodiment, a tuning procedure of the transform operator and of theweights may be carried out by comparison to a phantom, or to tissue, andidentifying (subjectively or objectively) the best result. In anembodiment, a tuning procedure of the transform operator and of theweights may be carried out by comparison against a known equation,matching the weights to the transducer and patient geometry, typicalfluence, etc.

In an embodiment, a transform operator may implemented by the followingequation:vout(t)=a(t)d/dt[b(t)vin(t)],where vin(t) is the input signal, vout(t) is the output signal, d/dt isa derivative operation, and a(t) and b(t) are constant functions. In anembodiment, a(t)=(t)² and b(t)=1/(t) to approximately represent asimplification for the integrand for a three dimensional case for a fullview reconstruction formula with part of the geometry weights foldedinto the a(t) term. Thus, the transform operator amplifies highfrequencies while not eliminating low frequencies in the signal. In anembodiment, a(t)=(t+α)² and b(t)=1/(t+α), where α is a small number toprevent division by zero. In an embodiment, the transform operator mayconsist of a sequence of convolution and signal multiplicationoperations in (or building upon) the form described above to approximatea closed-form inversion or similar equation. In an embodiment, thetransform operator alone may be applied on the acquired data as apre-conditioner for a reconstruction method or for other processing. Inan embodiment, the transform operator is used as a non-linearpre-conditioner prior to a sparse or quadratic minimization basedreconstruction algorithm, which may bring the data closer to thereconstructed form of the solution with the frequency componentsmatching the reconstructed geometry for faster convergence.

In an embodiment, to implement the transform operator formula indiscrete time, the derivative operation may be replaced with a finitedifference operation. In an embodiment, the value of t may be replacedwith kT, where T is the sample period (inverse sample rate), and kranges from 1 to the number of samples. In an embodiment, the transformoperation is performed on each channel.

The following processing steps are an illustrative embodiment ofapplying the transform operator to a set of data such as a sinogram:

-   -   a. Create a floating point time values squared array (TV2[ ]),        the array size being as large as the number of samples. The        elements in the time values squared array are populated with the        square of kT, where T is the inverse of the sample rate and k        ranges from 1 to the number of samples (i.e., the first value        TV2[0]=T*T, the second value is TV2[1]=2T*2T, etc.). For        example, with a sample rate of 100 Hz, this array would have        [0.0001, 0.0004, 0.0009, etc.].    -   b. Create a floating point time values reciprocal array (TVR[ ])        of the same size. The elements of the time values reciprocal        array are populated as the reciprocal of the corresponding time        values array entry (i.e., the first value TVR[0]=1/T, the second        value TVR[1]=(1/2T), etc.).    -   c. Create two floating point temporary arrays (T1[ ] and T2[ ])        of the same size.    -   d. Iterating over each channel:        -   i. Multiply each sample in the input signal (i.e., channel)            by the corresponding entry in the time values reciprocal            array (e.g., T1[n]=Input[n]×TVR[n]; then        -   ii. Form the finite difference between each multiplied            sample and preceding multiplied sample (e.g.,            T2[n]=T1[n]−T1[n−1], note, T2[0] may be set to zero as there            is no preceding sample)        -   iii. Form an output array by multiplying each finite            difference by the time value squared (e.g.,            Output[n]=T2[n]×TV2[n]            Image Reconstruction (225)

Above were discussed several optional processing steps for processingthe time domain optoacoustic return signal. For a variety of reasons,the two dimensional sinogram data as discussed herein is not susceptibleto closed form reconstruction because, among other reasons, complexitiesinvolving: tissue attenuation; frequency dependent tissue attenuation;in-homogeneities of propagation speed; and in-homogeneities for othertissue properties. Moreover, the transducer elements used to acquire thesinogram data are not ideal, i.e., perfect, but rather, have anelectro-mechanical frequency response that distorts the data. Thetransducer elements also have directivity and finite-aperture whichaffects the weighting of the measured signal strength corresponding toeach pixel, and the transducer array has a limited view. Further, insome circumstances, as discussed herein, the acquisition probe uses anacoustic lens to limit the opto-acoustic signal of 3D tissue to a 2Dimaging plane—suppressing out-of-plane signals—and thus, changing themathematical geometry. The dimensionality of the geometry represented bythe sinogram data does not conform neatly to a 3D case, a 2D case or acase with cylindrical symmetry.

Turning now to FIG. 4, an illustrative image reconstruction process isshown, including several optional steps. Several time-domain processingfunctions are discussed as part of image reconstruction, however, itshould be noted that there is no bright-line distinction to whenpreprocessing ends and image reconstruction begins. In other words, onecan consider preprocessing part of the image reconstruction process. Thedistinctions made herein between preprocessing and image reconstructionare merely for organizational convenience.

In an embodiment, raw or preprocessed sinograms may be further processedin the time domain, and an image reconstructed there-from. Furtherprocessing may, but need not include, extract quadrature (405) andsub-band acoustic compensation (345). Sub-band acoustic compensation wasdiscussed above, and will not be discussed again in detail—as discussedabove, the pre-reconstruction time domain signal processing order isgenerally flexible, and the various processes may be rearranged for avariety of reasons, including, without limitation, optimization, imagequality, coding convenience and processing considerations. Accordingly,in an exemplary embodiment, the transform operator (350) may beconsidered, and included, within the reconstruction block. There-ordering of the blocks may, or may not, yield identical results,accordingly, in an embodiment, the system described herein may beflexible enough to permit the operation of one or more of the blocks invarying sequences.

In an embodiment, each of the sinograms, e.g., each long and shortsinogram, is reconstructed. In an embodiment, as discussed in moredetail below, the long and short sinograms each result in two images,one processed from the real component of a complex sinogram, and onefrom the imaginary component of a complex sinogram. Once reconstruction(414), and thus image reconstruction (225), is complete,post-processing, i.e., image processing (230), as discussed furtherbelow, is performed on the resulting image or images.

Image Reconstruction (225)—Extract Quadrature (405)

When measurements are taken with a probe 102, the response of thetransducer may change the frequency domain phase of the optoacousticreturn signal. As an example, if there is a shift in phase of aparticular frequency component of the optoacoustic return signal, it mayinvert (negative) the corresponding portion of the signal in timedomain, and in effect, cancel a portion of the signal during aback-projection or other reconstruction process. Generally, however, aprobe can be calibrated by measuring how it changes the phase of asignal. Despite knowledge of how the probe changes the frequency domainphase, the phase of the optoacoustic return signal from tissue isunknown, and substantially unpredictable. The transfer functions of theacoustic paths between the locations of each acoustic source and eachtransducer element will change under varying mechanical conditions, andupon scanning different regions or types of tissue or between subjects.Thus, in this regard, frequency domain phase cannot be predicted evenwhere the probe's effect on phase were known precisely. The frequencydomain amplitude response from each acoustic source in the volume to thetransducer is also an unknown, however distortions resulting from themiscalibrated frequency domain amplitude response of the tissue are of adifferent nature, and in some cases may not cause the same degree ofproblems, or can be compensated for using other methods. In addition,the response function is different for the path from each position inthe tissue volume to each transducer. In all, there exist a large numberof unknown transfer functions for which to compensate.

Although it is not necessary to rectify the complex-valued analyticsignal prior to reconstruction, in an embodiment, to counteract thepotential unwanted distortions and cancellations that may affect thereconstruction process, the sinogram can be processed into an analyticrepresentation and stored as complex-valued array. With the negativefrequencies removed, the complex-valued analytic signal in thetime-domain will permit reconstruction of images that show instantaneousenergy representing the acoustic sources in the tissue more accurately.The result of a rectification prior to reconstruction is different froma post-reconstruction rectification (i.e., |z₁|+|z₂|+ . . .+|z_(N)|>=|z₁+z₂+ . . . +z_(N)| where z_(n) is a complex number and N isthe number of transducers). Said differently, if beamforming (i.e.,reconstruction) is performed on band-limited signals without taking theenvelope, ringing may occur in the reconstructed image. When the complexanalytic signal is used for reconstruction, however, the same ringingdoes not occur.

When the rectification is performed prior to reconstruction, nodestructive mechanism exists to cancel the signals, which tends toresult in high-contrast but also high streaking of the image, especiallywhere the view is limited. When the complex analytic signal isreconstructed, however, there is a destructive mechanism (which mayoperate based on coherence). Thus, in the formation of any pixel, whenthe contributing components of the signals line up, they will addconstructively but when signals are random or incoherent, which tends tooccur under a variety of circumstances (including when the sources havenot resulted from an acoustic source associated with the pixel beingreconstructed), they will tend to cancel out. In an embodiment, thiseffect may be used to produce higher quality images. In an embodiment, areal-valued non-analytic sinogram may also be used to form the image,the envelope of which may be extracted, if desired, post-reconstruction.In such embodiment, ringing associated with a real-valued band-limitedor filtered reconstruction may have occurred.

In an embodiment, an envelope can be extracted from the non-analyticreconstructed real image post-reconstruction. The envelope may beextracted by taking the envelope of a monogenic representation of theimage, which may be carried out by computing the Hilbert-transformeddirectional derivative surfaces of the horizontal and vertical lines ofthe image and then computing for each pixel the square root of thesquare of the horizontal component plus square of the vertical componentplus the square of the original image.

In an embodiment, an envelope image/auxiliary image can be formed bycomputing the envelope from every vertical line of the imagepost-reconstruction.

In an embodiment, to produce the analytic representation, the sinogrammay be transformed to the frequency domain, multiplied by a coefficientarray where the negative frequency components are zeroed and thepositive frequency components are doubled, and then returned to the timedomain, to form the complex-valued analytic representation. Theimaginary portion of the complex-valued time domain signal representsthe “quadrature” component and the real portion of the complex-valuedtime domain signal represents the “in-phase” component. The “quadrature”(i.e., imaginary) component, Q, is a function of the “in-phase”component, I, as follows: Q=H{I}, where H is the Hilbert transform. Inan embodiment, the Hilbert transform operator can be used to extract ananalytic signal representation from the real-valued data. In anembodiment, the Hilbert transform may be performed in the time domain orin the frequency domain. Transfer from the time domain to the frequencydomain may be done using a Fourier transform such as the Fast FourierTransform, and the return to the time domain may be accomplished by aninverse operation such as the Inverse Fast Fourier Transform.

In an embodiment, the in-phase and quadrature sinograms can go throughthe reconstruction process separately, each treated as an independent,real-valued constructions. In an embodiment, the in-phase and quadraturecomponents can be treated as a single, complex-value sinogram, with asingle reconstruction stage operating on complex data. In an embodiment,weighted delay-and-sum reconstruction (415) may be used to implement thereconstruction step. In an embodiment, the output of reconstruction(415) is treated as complex-value data, with in-phase and quadraturereconstructed components. In an embodiment, the Extract Quadrature (405)step uses as the real component input the (processed or unprocessed)sinogram, and returns an imaginary (quadrature) component sinogramhaving the same dimensions as the input sinogram, thus, together withthe source sinogram, forming a complex sinogram; each of the twosinograms may then be used to form a separate image, one of the realsinogram and one of the imaginary (quadrature) sinogram. In anembodiment, the complex sinogram may be used to form an image from thecomplex modulus of each complex value of the reconstructed compleximage, or, the square root of the real (in-phase) image componentsquared plus the imaginary (quadrature) image component squared.

In an embodiment, a two dimensional frequency domain transformcomprising a filtering operation is used to create a secondary imagefrom the complex image. In an embodiment the secondary image is createdfrom the complex image using a convolutional or FIR filter. As discussedin more detail below, in an embodiment, a series of processing steps maybe performed on the complex image prior to converting it, or rectifyingit, to a real valued image.

In an embodiment, the analytic representation of sinogram (with negativefrequencies removed) may undergo a shift in the frequency domain,corresponding to complex demodulation. In an embodiment, suchdemodulation may be used to further prevent ringing by bringing theoptoacoustic frequency content remaining after filtering towards DC. Inan embodiment, such demodulation may be used in conjunction with abandpass or smoothing filter to perform feature size selection, theoperation of demodulation assisting in the display of featuresassociated with a particular range of frequencies or scale. In anembodiment, frequency size selection may be tunable by an operator orselectable from a predefined list of settings.

Image Reconstruction (225)—Reconstruction (415)

Reconstruction (415) is a term used to signify the process of convertingthe processed or unprocessed data in the sinogram into an imagerepresenting localized features in a volume of tissue. In an exemplaryembodiment, reconstruction (415) can be based on a weighteddelay-and-sum approach. As discussed above, the weighted delay-and-sumalgorithm may optionally be preceded by a transform operator (350). Inan embodiment, the weighted delay-and-sum algorithm can operate oncomplex-valued data. In an embodiment, weights may be used byreconstruction (415) to represent the contributions from each sample tobe used for each pixel, and organizationally, the method used togenerate the weights may be considered part of image reconstruction(225). In an embodiment, the weights may be tuned based on an analysisof the collected data.

Generally, reconstruction (415) takes as input, processed or unprocessedchannel data, i.e., a sinogram, and uses this information to produce atwo dimensional image of a predetermined resolution.

The dimensions of an individual pixel (in units of length) determine theimage resolution. If the maximum frequency content in the sinogram datais too high for the selected resolution, aliasing can occur duringreconstruction. Thus, in an embodiment, the resolution and sampling ratemay be used to compute limits for the maximum frequency content thatwill be used in reconstruction, and thus to avoid frequency content thatis too high for the selected resolution. In an embodiment, the sinogramcan be low-pass filtered to an appropriate cutoff frequency to preventthe aliasing from occurring.

Conversely, if the sampling rate is too low to support the imageresolution, then, in an embodiment, the sinogram can be upsampled andinterpolated so to produce a higher quality images. While the twodimensional image can be any resolution, in an exemplary embodiment, theimage can comprise 512×512 pixels. In an another exemplary embodiment,the image can comprise 1280×720 pixels. In yet another exemplaryembodiment, the image may comprise 1920×1200 pixels. In an embodiment,the horizontal resolution is at least 512 pixels wide, but not more than2560 pixels wide, and the vertical resolution is at least 512 pixelshigh, but not more than 1600 pixels high.

A two dimensional image may represent variations in the volume, such asstructures, blood, or other inhomogeneities in tissue. Thereconstruction may be based upon the first propagation time from eachlocation in the tissue to each transducer and the contribution strengthof each sample to each pixel. The signal intensities contributing toeach pixel in the image are combined to generate the reconstruction.

The following processing steps are an illustrative embodiment of areconstruction algorithm using a weighted delay-and-sum technique:

-   -   a. Allocate an output image array and set all values to zero    -   b. For each transducer channel:        -   i. For each pixel in the output image array:            -   1. Access the delay (in samples) from Sample Delay Table                for that channel and pixel, and then retrieve the sample                (from the sinogram) corresponding to the channel and                delay            -   2. Access the weight from Weights Table corresponding to                the channel and pixel            -   3. Multiply the sample by the corresponding weight            -   4. Add and store the result with in location of the                output image array corresponding to the destination                pixel.

The weights table is a table representing the relative contribution ofeach sample in the sinogram to each pixel in the resulting image. In anexemplary embodiment, for relative computational efficiency, the sameweights table can be used for the real and imaginary components of acomplex sinogram. In an embodiment, separate weights table can be usedfor each of the components of a complex sinogram. In an embodiment, onecomplex weights table can be used for the real and imaginary componentsof a complex sinogram. In an embodiment, separate complex weights tablecan be used for each of the components of a complex sinogram. In anembodiment, a complex weights table can be used to account forstanding-wave type patterns in the image that are the result of thesystem geometry.

The weights table can be used to establish something akin to an aperturein software. Thus, in an embodiment, where a wider aperture is desired,more weight is given to off-center samples. Stated in other words, forexample, for a given transducer, usually no sample would be given moreweight than the sample directly beneath the transducer, and for thepurposes of illustration, consider that the weight for a given sampledirectly beneath the transducer is 1. Consider further the relativecontribution of samples that are at 15, 30 and 45 degrees from center,but equidistant from the transducer. To narrow the aperture, thosesamples could be weighted 0.5, 0.25 and 0.12 respectively, while towiden the aperture, those same samples could be weighted 0.9, 0.8 and0.7 respectively. The former would provide only a slight (12%) weight tosamples received from a source at 45 degrees from center, while thelatter would provide the same sample much higher (70%) weighting. In anembodiment, the system displaying the optoacoustic output—which may, butneed not be the same as the system acquiring the sinogram—would providethe operator the ability to vary this parameter (i.e., the softwareaperture) when viewing optoacoustic images.

In an embodiment, a very large table contains a mapping of relativeweight and delay for each pixel and transducer. Thus, in an embodimentwhere a target image is 512×512 pixels and the probe 102 has 128channels (i.e., transducers), there are 33,554,432 weight entries andthe same number of delay entries. Similarly, in an embodiment where atarget image is 1280×720 pixels and the probe 102 has 128 channels(i.e., transducers), there are 117,964,800 of each type of entry. In anembodiment where a target image is 1920×1200, and the probe has 256channels, there are almost 600 million entry of each type.

As discussed above, the extract quadrature step (405) provides animaginary component sinogram, and in an embodiment, each of the real andthe imaginary component sinograms may be reconstructed into an image,thus producing two images, one for each component of the complexsinogram. In an embodiment, delay and weight tables are the same foreach component of the complex sinogram. In an embodiment, the delaytable is the same for each component of the complex sinogram, but theweight table is different for the real and imaginary componentsinograms. In an embodiment, the weight table is the same for eachcomponent of the complex sinogram, but the delay table is different forthe real and imaginary component sinograms.

Image Reconstruction (225)—Calculate Weights and Delays

As discussed above, in the illustrative embodiment of a delay-and-sumreconstruction algorithm, a Weights Table may be employed. An algorithmmay be used to calculate the Sample Delay Table and Weights Table foreach transducer. In an embodiment, the data comprising Sample DelayTable(s) correlates the estimated contribution of each transducer toeach pixel, while the data comprising the Weight Table(s) provides anestimate of the relative weighting of the contribution of eachtransducer to each pixel as compared to the other contributions to thatpixel. In an embodiment, the Weights Table may be used to account forangular apodization with respect to the transducer's norm, power of thelaser, time gain control, light attenuation within the tissue, skinthickness, coupling medium characteristics, patient specific variables,wavelength specific variables and other factors.

In an embodiment, each of the tables corresponds in size (in pixels) tothe two dimensional image output by image reconstruction, and aplurality of each table are created, one for each channel. In theillustrative embodiment above, each Sample Delay Table correlates thepixels of the target image with the samples in an sinogram, thus, oneSample Delay Table (which is specific to a channel) will identify foreach pixel in the image, the specific sample number in that channel thatis to be used in calculating that pixel. Similarly, in the illustrativeembodiment above, each Weights Table correlates the pixels of the targetimage with the weight given to the sample that will be used; thus, oneWeights Table (which is specific to a channel) will identify for eachpixel in the image, the weight to be given to the sample from thatchannel when calculating the pixel.

X- and Y-coordinates of the image pixels are calculated using the inputinformation on the image size and location. The time delays arecalculated for each transducer and each pixel by knowing the distancebetween pixel and transducer and the speed of sound. If an acousticmatching layer with different speed of sound is used, then separate timedelays are calculated inside and outside of the matching layer and addedtogether, resulting in the overall transducer-pixel delay. The weightsare calculated for each transducer and each pixel, depending on theirrelative location. The distance and angle between the transducer-pixelvector and transducer's norm are taken into account, as well as thedepth position of an individual pixel. In an embodiment, the systemcalculating the weights and/or delays—which may, but need not be thesame as the system acquiring the sinogram or displaying the imagesreconstructed there-from—would provide the operator the ability to varyparameters used in processing. In an embodiment, the system calculatingthe weights would provide the operator the ability to vary the bases forthe weight calculation, thus, e.g., giving more or less weight tooff-center acoustic data. In an embodiment, the system calculating theweights would provide the operator the ability to controls whetherlinear or power relationships are be used in calculation of the weights.

Pseudo-code in the Appendix will provide a guide for a person ofordinary skill in the art in implementing an illustrative algorithm tocalculate weights and delays.

Once reconstruction (414), and thus image reconstruction (225), iscomplete, post-processing, i.e., image processing (230), may beperformed on the resulting image or images.

In an embodiment, image reconstruction may be based on AdaptiveBeamforming, Generalized Sideband Cancellation, or other methods as areknown in the art. In an embodiment, techniques for reconstruction may bebased on determining cross-correlations functions between channelsand/or maximizing the sharpness objective of the image.

In an embodiment, a method to reconstruct a volume may consist ofdecomposing a cross-section or volume into radial wavelets, the radialwavelets representing optoacoustic sources (the measured optoacousticreturn signal of radial optoacoustic sources in particular are presumedto obey a simple closed form equation), the technique ofWavelet-Vaguelette decomposition may be used to relate the wavelets andvaguelettes between the image domain and the sinogram and to therebydetermine the intensities of the radial wavelets in the image, and thusto reconstruct the image. In an embodiment, the projection of radialwavelets from the image domain into the sinogram domain (i.e.,vaguelettes) can be used in conjunction with other image formationtechniques prior to determining the intensities of the of the radialwavelets. In an embodiment, adaptive beamforming, or wavelet de-noisinginvolving thresholding can be performed on the radial-waveletprojections as a stage such a reconstruction.

In an embodiment, reconstruction may be based on Iterative Minimizationor Iterative Maximization, such as, for example, L1-minimization orL2-minimization. Iterative Minimization algorithms for reconstructionand enhancement require high computational load and thus, are notconsidered applicable for real-time imaging. Real-time optoacousticreconstruction of a cross-section of a volume can be performed using anL1-minimization algorithm. In an exemplary embodiment for performingL1-minimization reconstruction in real-time on a 2D cross-section of avolume, the Fast Wavelet Iterative Thresholding Algorithm is used, andcombined with the Helmholtz wave equation in the frequency-domain, whichcan be efficiently used to represent optoacoustic wave propagationyielding a diagonalizable (or nearly diagonalizable) system matrix. Inan embodiment, the pixels of the image may be decomposed into radialwavelets, the decomposition represented in the frequency domain asradial subbands, and the radial subbands used in the iterativethresholding. In an embodiment, the Fast Wavelet Iterative ThresholdingAlgorithm may be used where the system matrix is found empiricallyrather than through using an ideal equation.

When the laser illuminates the volume of tissue with at least a portionof the surface being adjacent to a medium that is not perfectly matchedto the acoustic properties of the volume, the propagating acoustic wavemay reflect—at least in part—off the unmatched surface and propagateinto the volume as an incident wave-front. The incident wave-front canfurther reflect off acoustic discontinuities in the tissue and interferewith the optoacoustic return signal creating an artifact. This artifactcan be separated from the optoacoustic return signal using, e.g., aninteractive minimization technique. In an embodiment, an image mappingthe intensity of this artifact can be produced.

In an embodiment, a pattern detection classifier can be applied to anoptoacoustic return signal, wherein the classifier output reflects thestrength of a particular indicator as a function of time (or distance).Accordingly, upon obtaining measurements from multiple transducerpositions, the classifier output can be beam-formed to localize thesource (i.e., phenomenon) causing the pattern detected. An imageproduced from the beam-formed classifier output may suffer fromblurring, reconstruction artifacts, and streak artifacts, which may beparticularly acute in a limited-view case. These artifacts may result atleast in part because the pattern classified signal may lack informationconcerning signal strength that is part of a non-pattern classifiedsinogram, and its intensity is related to the presence of the pattern,not necessarily on the distance that the transducer is located from thesource of the pattern. The classifier output of a classifiedoptoacoustic signal, however, can be “fit” into the propagation model ofthe Helmholtz equation where the classifier output is characterized asoriginating from an instantaneous source term at a given position. Thus,to reduce the streaking, blurring and artifacts a parametric map of thepattern classified signal can be formed using techniques forreconstruction and deconvolution other than simple beamforming.Application of, e.g., an iterative minimization technique can be used toreduce streaking and thus better localize the source of the pattern.Different types of classifiers and reconstruction techniques may havedifferent considerations that apply. In an exemplary embodiment, aparametric map of the classified quantity can be produced by using aniterative minimization technique, where the system matrix is formed asit would be had the source been an optoacoustic signal. In anembodiment, the sparse basis representation used by, e.g., L1minimization, may serve to localize the source of the pattern and hencereduce artifacts. Thus, rather than applying the reconstructiontechnique to an optoacoustic return signal, it may be applied toclassifier output, where the classifier output is represented in theform of a sinogram. In an embodiment, the reconstruction technique isapplied as though the classifier output were an optoacoustic returnsignal. In an embodiment, further processing, such as taking a complexenvelope of the classifier output, filtering, or deconvolving theclassifier output may be performed prior to reconstruction. In anembodiment, the classifier may be designed to discriminate betweennormal and abnormal branching blood vessels in tissue.

Image Processing (230)

As discussed above, after the long and short sinogram are acquired (205,210), optionally preprocessed (220) and then image reconstructed (225)to form images, certain post processing may be performed on theresulting images. Turning now to FIG. 5, optional post-processing stepsare shown, including remove inter-frame persistent artifact (505),fluence compensation (510) and complex magnitude (515). In anembodiment, image processing produces an envelope image (520) that ispositive real valued (not complex-valued).

Image Processing (225)—Remove Inter-Frame Persistent Artifact (505)

The optoacoustic return signal comprises both desirable and undesirableinformation, among the information that may be undesirable is what willbe referred to herein as the undesired coupled response. The undesiredcoupled response may include artifacts that result from light striking aperson's skin as it penetrates into the tissue. More generally, theundesired coupled response being addressed by this step is inter-framepersistent signal or inter-frame persistent artifact. Inter-framepersistent signal, as used herein, refers to an interfering signal thatremains constant, or changes very slowly, and which is thereforepresumed to produce similar interference in each of a plurality ofimages that are spatially and/or temporally related. Inter-framepersistent artifact refers to the same phenomenon, but when it appearsin a reconstructed image. Thus, the terms inter-frame persistent signaland inter-frame persistent artifact may sometimes be interchanged hereinbecause they represent the same phenomenon. The problem of removinginter-frame persistent signal is complicated by the fact that thesimilar interference found in separate frames may be scaled in amplitudeby a constant factor. The scaling may be related to a number of factors,including, without limitation variation in the total light energy usedto cause the optoacoustic return signal. Moreover, generally,inter-frame persistent signal varies sufficiently from person to person,that it is not readily identifiable except by examination of a pluralityof frames for a given individual. In an embodiment, a plurality offrames taken in relatively close spatial and/or temporal proximity toeach other, but generally not in an identical location, are analyzedwith the goal of removing inter-frame persistent signal.

In an embodiment, in a first process directed to the removal ofinter-frame persistent signal, a step is performed to estimate itscomposition. In an embodiment, an inter-frame persistent signal is takenas the first principal component from a set of independent frames. Thefirst principal component can be computed using any method, although, inan embodiment, the first principal component can be computed using SVD(singular value decomposition) or an equivalent iterative method.

In an exemplary embodiment, the set of independent frames is selectedsuch that each frame has independent background noise. In other words,generally, independent frames taken when the probe 102 is not movingshould not be included in the set. Accordingly, in an embodiment, eachsequential frame that may be considered for use in the set may beflagged to indicate its suitability (or to indicate its non-suitability)for inclusion in the set. To analyze a frame for suitability ornon-suitability for inclusion in the set, the frame may be compared toone or more frames preceding it in sequence. The flagging of a frame (assuitable or non-suitable) may be done at capture-time, or thereafter,but prior to the step estimating the inter-frame persistent signals. Inan embodiment, the flagging of a frame (as suitable or non-suitable) isperformed prior to writing that frame to the LOM file. In an embodiment,the process of estimating the inter-frame persistent signals may includea frames selection sub-step.

The following processing steps are an illustrative embodiment of aninter-frame persistent signal estimator:

-   -   a. Initialization (enter if sizeOfFrameBuffer has changed, or Nr        (number of rows in frame) or Nc (number of columns in frame) has        changed)        -   i. For each channel, allocate a frameBuffer as a circular            buffer to have sizeOfFrameBuffer frames.        -   ii. Set frameBuffer.start[channel] to 0 and            frameBuffer.end[channel] to 0 for each channel. These two            variables keep track of the active frames in the circular            buffer.        -   iii. For each channel allocate estimate[channel][Nr][Nc] and            set all elements to 0.    -   b. If captureFrame is true (thus the frame is flagged as        suitable for inclusion in the set) then        -   i. Optionally, apply an image transform to frame_in (e.g., a            two dimensional wavelet transform, a two dimensional FFT, or            another similar transform; a band pass filter may be applied            to remove certain frequencies from the computation)        -   ii. Add frame_in to the frameBuffer for the current channel.            If the buffer is full overwrite the oldest frame in the            buffer.    -   c. If computeFrame is true then        -   i. Map all of the data in frameBuffer into a matrix where            each frame in the buffer is treated as a column and each row            is a value of the same pixel index.        -   ii. Compute the principal component (or independent            components) of frameBuffer for the current channel.        -   iii. (If an image transform was applied to frame_in, apply            the inverse transform to the results of the previous            calculation.    -   d. Output estimate_out for the current channel as the selected        principal component (or independent component), absent an        alternative selection, the first principal component is        selected.

In connection with the foregoing process steps it should be noted thatfor optimization of step c(ii), computation of the full SVD may not bereal-time. It is not necessary that the persistent frame estimationprocess run on every frame. In an embodiment, the persistent frameestimation process may be re-updated periodically, e.g., based on atrigger external to the algorithm. In an embodiment, it may bebeneficial to run persistent frame estimation process in a thread andutilize the most recently finished estimate only. In an embodiment, thefirst principal component is found in the complex domain, thus, the SVD(or other) function should accept complex-valued input. In anembodiment, the inter-frame persistent signal estimate should have azero mean, and unit L2-norm. In an embodiment, only the first principalcomponent is computed. In an exemplary embodiment, the first principalcomponent is computed for the estimate on the complex image using apower iterative method for efficiency. In an embodiment, the interframepersistent signal estimate is the first several principal components. Inan embodiment, the interframe persistent signal estimate is the firstseveral independent components. In an embodiment, when multipleestimates are generated, each is removed from the signal. In anembodiment, the inter-frame persistent estimate can be performed in animage transform domain, such as a two dimensional wavelet transformdomain or two dimensional FFT transform domain, as discussed above. Inan embodiment, the inter-frame persistent estimate can be performed on aband-passed set of data.

Once the inter-frame persistent signal is estimated, it can be removedfrom the frames. In an embodiment, the inter-frame persistent signal maybe subtracted from the frame. As discussed above, although theinterference may be identical from frame to frame, it may be scaled inamplitude. Thus, in an embodiment, prior to subtraction of theinter-frame persistent signal estimate from the source frame, a scalingfactor should be computed, and the scaling factor may be used to scalethe estimate so that it can be subtracted from the source frame. Thescaling factor is the projection of the inter-frame persistent signalcomponent. In an embodiment, multiple inter-frame persistent signals maybe estimated. In an embodiment each of the multiple inter-framepersistent signals may correspond to the highest energy components inthe decomposition method used to perform the computation (e.g., first 3SVD components).

Image Processing (230)—Fluence Compensation (510)

Because skin and tissue characteristics vary from patient to patient,light distribution in the tissue of a specific patient cannot bepredicted. The fluence profile of the light can be broken down into aspatially-dependent common light penetration profile component and twospatially-dependent wavelength-specific fluence-ratio profiles, whichrelate the true fluence to the common light penetration profile. In anembodiment, the common light penetration profile and wavelength-specificfluence-ratios may be used to compensate for patient specific variationthat affect the distribution of light within the tissue. In anembodiment, 1-dimensional curves based on a model of fluence behaviorfor the common profile and specific profile, may be used, with a singlepatient specific parameter, to generate the two dimensional fluencecompensation curves. In an embodiment, any of the following equationsmay be used without limitation as for compensation curves:

Type Equation LINEAR f(x, g) = 1 + g * x EXPONENTIAL f(x, g) = exp(g *x) EXPONENTIAL_DIV f(x, g) = x * exp( g * x) IDENTITY f(x, g) = 1

Other equations or simulated curves may be used for the compensationcurves. In an embodiment, experimentally measured fluence distributioncurves can be used as a method of compensation. In an embodiment, anseparate device or a separate sensor (that may use optoacousticprinciples) can be employed to measure the fluence curves in real-timeduring the light event. In an embodiment, the fluence compensationcurves can be derived (i.e., estimated) from simulations. In anembodiment, the reciprocal (or modified reciprocal) of a measured orsimulated curve may be used as a one dimensional fluence compensationcurve. In embodiment, a measured or simulated curve may be filteredprior to being used in fluence compensation. In an embodiment, fluencecompensation curves based on statistical features may be computed as afunction of depth in a single image or in a set of images dynamicallyacquired.

Turning now to FIG. 6, a set of process steps for fluence compensation(510) is shown. In an embodiment, the system performing processing onthe optoacoustic data, and/or the system displaying the optoacousticoutput—which may, but need not be the same as the system acquiring thesinogram—would provide the operator the ability to select betweenavailable equations, and select a parameter used for processing anoptoacoustic image or its derivative for viewing. Thus, in anembodiment, an operator may select a curve, such as the exponentialcurve, and/or a parameter, such as the exponent. In an embodiment, thecurve, and possibly the parameter, are selected from a finite list ofselections presented to the operator in a user interface. Once the curveand parameter are selected, the common fluence curve (605) andwavelength specific curves (610) are calculated. Thereafter, in anembodiment, a two dimensional (e.g., a curve for each pixel column)overall fluence normalization curve (615) is computed. The twodimensional overall fluence normalization curve is then applied to theimage (620). In an embodiment, the compensation curves are automaticallyselected from a set of compensation curves based on image statistics orstatistics of a region of interest within the reconstructed image. In anembodiment, the fluence compensation curve may be computed based on aregion-of-interest identified in real-time by a system operator, thefluence compensation curve being dependent on a measure of depth of theidentified region-of-interest. In an embodiment, a region-of-interestmay be identified by selecting a rectangular region-of-interest of atarget object, the center of the region corresponding to the depth usedto determine the compensation curve.

The following processing steps are an illustrative embodiment ofproducing a two dimensional fluence compensation curve from a selectedone dimensional equation applicable for an ideal linear array andapplying it to an uncompensated image:

-   -   a. Compute one dimensional array containing the depths for each        pixel in the image starting at the minimum image depth until the        maximum image depth. Store the result in the vector “x”.    -   b. Calculate one dimensional common fluence compensation curve        based on the common gain parameter “g₀” using a selected        compensation function for f₀(x,g₀) for the fluence compensation.    -   c. Calculate one dimensional channel-specific compensation        curves for each channel        -   i. The channel 1 curve is based gain parameter “g₁” using a            selected compensation function for f₁(x,g₁) for the fluence            compensation.        -   ii. The channel 2 curve is based gain parameter “g₂” using a            selected compensation function for f₂(x,g₂) for the fluence            compensation.    -   d. Calculate the overall two dimensional normalization curves        from the one dimensional common curve and channel specific        curve.        -   i. For each channel, create an overall one dimensional curve            by multiplying the common curve with the channel specific            curve        -   ii. Set each vertical column in the two dimensional            normalization curve equal to overall one dimensional curve    -   e. For the current channel reconstructed image        -   i. for each pixel in the image, multiply the value of the            pixel by the corresponding pixel in overall two dimensional            normalization curve belonging to the current channel

In an embodiment, Fluence Compensation (510) may process the compleximage, and provides a new complex image as its output. In an embodiment,Fluence Compensation (510) may process a real image, and provides amodified real image as its output.

Image Processing (230)—Complex Magnitude (515)

In an embodiment, the complex magnitude (515) step takes as input thecomplex image (or a real image where the imaginary component is notavailable), and produces an envelope image that has the same number ofrows and columns as the input image. The envelope image may bedetermined by taking the complex magnitude of each element of the input.Where the real image alone is available, the envelope image is theabsolute value of the information in that image. In an embodiment, theenvelope can be computed alternately from the real image alone byproducing an image in substitute for the imaginary component image whereeach vertical line in the imaginary image is the Hilbert transform ofthe corresponding line in the real image; the complex magnitude beingapplied in the same way.

Generate Parametric Images (240)

As discussed above, after the long and short sinogram are acquired(steps 205, 210), optionally preprocessed (step 220) reconstructed (step225) to form images, and processed (step 230) to produce short (232) andlong (234) envelope images, the envelope images are used to generateparametric images (step 240), and more specifically, to generate one ormore of the following parametric images: an oxygenation map (250), ahemoglobin map (255) and a masked oxygenation map (260). In anembodiment, parametric images are presented by providing a colorizedimage reflective of qualitative information obtained from within theshort and long envelope images (232, 234).

Turning now to FIG. 7, the short envelope image (232) and long envelopeimage (234) are processed to provide at least one of the parametricimages (250, 255, 260). In an embodiment, the short envelope image (232)and long envelope image (234) may be processed by motion and tracking(705) to improve the signal to noise ratio and/or provide betteralignment between the images. In an embodiment, the short envelope image(232) and long envelope image (234) are processed by oxygenation andhemoglobin calculation (720) to produce grayscale maps of oxygenationand hemoglobin. More generally, a plurality of parametric maps (i.e.,two or more) may each be formed from the information in a plurality ofimages (i.e., two or more), and another parametric map may be formedfrom the information in at least two of the plurality of parametricmaps. It is within the scope of this disclosure that, rather thanforming another parametric map from the information in at least two ofthe plurality of parametric images, such latter parametric map may becreated directly from the information in the plurality of images. Inother words, in cases where mathematics does not require the creation ofthe intermediate parametric maps, should the only reason to do so be tocombine them into the latter combined parametric map, the separate stepof producing the intermediate maps may, in an embodiment, be omitted.

Once created, parametric maps may be denoised (735). In an embodimentthe grayscale maps are statistically color mapped to produce color mapsof oxygenation (250) and hemoglobin (255). The hemoglobin map (255) maythereafter be in combination with the oxygenation map (250) to provide amasked oxygenation map (260) in the combine transparency mask (750). Inan embodiment, the result of Generate Parametric Images (240) is an RGBAoxygenation map an RGBA hemoglobin map and an RGBA HgO maskedoxygenation map. As discussed above, in an embodiment, the color mappedquantity similar to the masked oxygenation map may be generated directlyfrom the data in the two envelope images, rather than passing throughthe intermediate stage of combining the transparency channels of theoxygenation map and hemoglobin map.

Generate Parametric Images (240)—Motion and Tracking (705)

Motion and tracking (705) may be necessary because, as successive imagesof a static (or slow moving) scene are generated, motion in the sensorwill cause the position of content of the scene to “move” relative toeach other. Thus, a subsequent image, g_(b), taken a short time (e.g.,100 ms) after a previous image, g_(a), may be offset by a number ofimage pixels in the horizontal and vertical dimension from the previousimage, g_(a). Similarly, subsequent images may also be subject tonon-rigid deformations that can occur between frames. In an embodiment,corrections may be made for non-rigid deformations. Moreover, in anembodiment, further motion and tracking may be employed to determine howthe probe is moving, thus providing a basis to generate a 3D image ofthe tissue structures. In an embodiment, and as discussed in more detailbelow, the system may include sensors (e.g., accelerometers, or fixedpositions sensors and targets, or otherwise) that will provide dataconcerning the position or movement of the probe during imaging. Suchinformation concerning position or movement may be taken into account inmaking correction for translation, rotation, angular deflection, orother probe movement that may cause deformations from frame to frame.

Turning briefly to FIG. 8, in an embodiment, the step of motion andtracking (705) is broken out into component parts, which may includemotion estimation (810), persistence (820) and alignment (830). In anembodiment, the motion estimation (810) process may be used to estimatemotion between two images. In an embodiment, the rigid motion betweenthe images is assumed to have no rotational component of motion. In anembodiment, the rigid motion between the images may be assumed to have arotational component of motion. In an embodiment, the persistence (820)process may be used to improve the signal to noise ratio. In anembodiment, the alignment (830) process aligns two images, such as ashort envelope image (232) and a long envelope image (234).

Motion estimation (810) can provide information that may support one ormore methods of removing the effect of probe motion between successiveimage acquisitions. In an illustrative embodiment, motion estimation(810) estimates motion that occurred between a short envelope image(232) and a long envelope image (234). In an embodiment, the motionestimation (801) process requires input of the number of rows andcolumns in the image, as well as cutoff values for a raised cosineapodized bandpass filter. In an embodiment, a filter array is created onstartup, or whenever there is a change to the input parameters. Thefilter array may be created by determining the 2D frequency components,and then using a raised cosine apodization function to smoothly shapethe bandpass characteristics of the filter and/or o that the bandpassrange corresponds to frequencies relevant to features that are tracking.In an embodiment, using a raised cosine apodization function creates aradial 2D bandpass filter in the frequency domain to suppress componentsthat are less likely to correlate in the motion estimation procedure,which may depend on the specific nature of optoacoustic scans. Acorrelation array computed using a buffered image and another image maythen be determined, and correlation determined there-from. In anembodiment, a phase correlation algorithm may provide a frequency domainapproach to estimate the relative positions of the content of twoimages. In an embodiment, given two input images, g_(a) and g_(b), takena short time apart, and where G_(a)=F{g_(a)}, and G_(b)=F{g_(b)}, andwhere F{g}=2D Fourier Transform if image g, the cross-power spectrum ofthe phase, R can be formed as follows:

$R = \frac{G_{a}G_{b}^{*}}{{G_{a}G_{b}^{*}}}$a normalized cross-correlation, r, can be provided by using the inverseFourier Transform:r=F ⁻¹ {R}and the offset, in pixels, is equal to the location of the peak in r:(Δx,Δy)=argmax_(x,y) {r}.In an embodiment, filtering (2-D) or zero padding in the edges may beapplied to the images (before the Fourier transform) to compensate foredge effects. In an embodiment, a small constant may be added to thedenominator of the cross-power spectrum term R, to serve as a filter forweak values, and/or to prevent division by zero. In an embodiment abandpass filter (i.e. the 2D radial raised-cosine apodized frequencydomain bandpass filter described above) may be multiplied with thenumerator of the cross-power spectrum.

In an embodiment, the motion is expressed in horizontal and verticalpixels, and may be provided along with additional correlation values.The correlation values may be expressed in a variety of ways, and in anembodiment, is expressed by providing a mean value of the absolute valueof the cross correlation array along with the maximum value of theabsolute value of the cross correlation array.

The following processing steps are an illustrative embodiment of motionestimation:

-   -   a. Create (or recreate) a filter array based on the input        parameters, by:        -   i. Getting the radial frequency components,        -   ii. Using a raised cosine apodization function to create a            bandpass filter array;    -   b. Determine the correlation between the previous frame (stored        in prior iteration of algorithm) and the current frame, and        calculate the translation offset vector;    -   c. If the value of the correlation is lower than a threshold,        and the translation is also lower than a threshold, the motion        can be assumed perpendicular to the imaging plane;    -   d. Store the current frame as the “previous” frame;    -   e. The probe velocity may be estimated from the translation        using the time elapsed between the frames;    -   f. In an embodiment, the translation or velocity outputs may be        low pass filtered to have a smoother estimate of velocity.

In an embodiment, once motion is estimated, a persistence (820) processmay be run to filter out noise and strengthen the true signal in theimage. The persistence (820) process presumes that unwanted signal,e.g., noise, may be present in the image, than the unwanted signal willchange from frame to frame. In an embodiment, the unwanted signal may bemodeled as Gaussian white noise. In an embodiment, it is assumed thatthe two images upon which the persistence (820) process is run will behighly correlated, making the change in true image content from frame toframe small. It will be apparent to a person of skill in the art thatthe lower the change in true image content, the better the results thatwill be achieved.

In an embodiment, the persistence (820) process performs a weightedmoving averaging (WMA) on image data, where one or more previous framesare weighted and considered with the image. In an embodiment, the weightgiven to previous frame or frames may depend on a single inputparameter. In an embodiment, the weight given to previous frames maydepend on a plurality of parameters. In an embodiment, the persistence(820) process performs exponentially weighted moving averaging (EWMA) onimage data, which is a type of (infinite impulse response) IIR filter.Using an IIR filter, instead of a finite impulse response (FIR) filterpermits storing less data in memory for calculation, such as, forexample, having only an array of the image, and an array for previousframes in memory.

In an embodiment, for a sample, n, the output value, y[n] is calculatedfrom an input value x[n] and the previous output value y[n−1] asy[n]=(1−α)x[n]+α y[n−1]. If n<0 then y[n]=0.

The following processing steps are an illustrative embodiment ofpersistence:

-   -   a. During initialization or if the image size has changed        -   Allocate and initialize an array called persistence_buffer    -   b. If translational motion has been detected (and the buffer is        not being flushed)        -   i. shift the persistence buffer for the current channel            using linear translation the detected amount    -   c. For each pixel in the input image        -   i. If the persistence buffer is not being flushed, then            -   persistence_buffer[channel][pixel]=(1-alpha)*input_image[pixel]+alpha*persistence_buffer[channel][pixel];        -   else            -   flush the persistence buffer for the channel by setting                the value of the input image pixel e.g.,                persistence_buffer[channel][pixel]=input_image[pixel];        -   ii. output_image[pixel]=persistence_buffer[channel][pixel]

In an embodiment, once the persistence (820) process is run, analignment (830) process may be used to align the present image and theprior one. In an embodiment, the alignment (830) process may rely uponthe results (e.g., horizontal and vertical pixel calculations) of motionestimation (810). In an embodiment, the alignment (830) process mayestimate the movement between the previous frame and the frame underconsideration. The alignment (830) process provides an output imageshifted by a vertical and/or horizontal offset. In an embodiment, thevertical and/or horizontal offset is provided in pixels. In anembodiment, the motion estimate for the persistence process uses phasecorrelation information from the images of similar wavelength channels,since images from similar channels will have the most similar featuresfor performing motion estimation. In an embodiment, the alignmentprocess runs on images of dissimilar wavelength channels since theimages from dissimilar channels should be aligned prior to calculation.

In an embodiment, the motion estimate and correlation are used toautomatically detect frames used by the interframe persistent artifactestimation procedure.

Generate Parametric Images (240)—Oxygenation and Hemoglobin Calculation(720)

After motion and tracking (705) an aligned short envelope image (710)and an aligned long envelope image (715) can be processed usingoxygenation and hemoglobin calculation (720) to produce a grayscaleoxygenation map (725) and a grayscale hemoglobin map (730). Generally,optical absorption in blood is different at differing wavelengths oflight. Moreover, optical absorption in blood is affected by bloodoxygenation. Because of the coefficient of absorption, at somewavelengths of light, blood of a given oxygenation is moreoptoacoustically responsive than blood at a lower oxygenation, while atother wavelengths of light, the reverse is true. For example, oxygenatedblood is less optoacoustically responsive than deoxygenated blood inresponse to stimulus from an Alexandrite laser, which has predominantoutput at about a 757 nm wavelength, while blood oxygenated blood ismore optoacoustically responsive than deoxygenated blood in response tostimulus from an Nd:YAG laser, which has predominant output at about a1,064 nm wavelength.

Turning to FIG. 9, and as discussed in more detail below, a hemoglobinmap and an oxygenation may be computed using information about theabsorption coefficients for deoxy-hemoglobin and oxy-hemoglobin at theshort and long wavelengths. Because the penetration of light into tissuecan vary, in an embodiment, the light penetration may be statisticallynormalized (normalize fluence (910)), In an embodiment, lightpenetration may be statistically normalized within a region of interest(ROI). In an embodiment, smoothing (920) may be applied. In addition, inan embodiment, oxygenation calculation (940) (but not hemoglobincalculation (950)) may be enhanced by a noise removal (930) process. Inan embodiment, either hemoglobin and/or oxygenation calculations may beenhanced by a noise removal process

In an embodiment, the system performing processing on the optoacousticdata, and/or the system displaying the optoacoustic output—which may,but need not be the same as the system acquiring the sinogram—wouldprovide the operator the ability to select a region of interest. In anembodiment, a graphical user interface would permit the user to identifya region of interest within, e.g., an ultrasound or optoacoustic image.In an embodiment, the ROI is a rectangular region. In an embodiment, theROI may be non-rectangular. In an embodiment, the ROI is specified by avalue, e.g., a Boolean value, for each pixel in the image and/or in theresulting parametric map to indicate if that pixel is part of thecomputational region of interest; in this way, the calculation is notlimited to performing on rectangular shapes. In an embodiment, aseparate ROI may be used for display purposes, thus, for example, oneROI may be used computationally, and a separate ROI may be used as aboundary display in the displayed image. In other words, thecomputational ROI and the display ROI need to be the same ROI.

In an embodiment, the fluence in the ROI within the short envelope image(232) and the long envelope image (234) may be statistically normalized.In an embodiment, the fluence in the ROI within the short envelope image(232) and the long envelope image (234) may be statistically normalizedusing a mathematical function. In an embodiment, to statisticallynormalize each pixel with the ROI of an envelope image, the value ofthat pixel is divided by the standard deviation for pixel values in theROI. This normalization method is used to compensate for variation inthe actual fluence of light on a specific target within the tissue,because the actual fluence is unknown, and may vary from person toperson as well as from laser event to laser event. Once statisticallynormalized the ROI generally reflects qualitative information concerningthe target tissue or volume. The physical justification for thenormalization is not based on OA principles, but rather, the effect ofthe operation is to normalize the histogram of each of wavelength in theregion of interest, based on an observation that the width(standard-deviation) of the histograms for each wavelength tend to beinvariant under certain conditions. Moreover, although the laser fluencemay not be accurately quantified at depth, the histogram width betweenwavelengths is believed to have some general stability with regard toother unknowns.

In an embodiment, smoothing (920) may be performed on the images via atwo dimensional convolutional filter. In an embodiment, the twodimensional convolutional filter kernel may be based on an adjustableparameter. In an embodiment, the filter kernel parameter defaults toGaussian. In an embodiment, the Gaussian or other filter kernel isseparable which may permit more efficient implementation. In anembodiment, the smoothing kernel may provide a facility to permit focuson objects of a particular size or scale, which may be related to afeature-size selection. In an embodiment, a feature-size selectionkernel may be a bandpass filter. In an embodiment, the system performingprocessing on the optoacoustic data, and/or the system displaying theoptoacoustic output—which may, but need not be the same as the systemacquiring the sinogram—would provide the operator the ability to selectthe adjustable parameter upon which the two dimensional convolutionalfilter kernel is based. The filter kernel may be applied to parametricimages or to the envelope images or to the complex-valued image. In anembodiment, the filter kernel may be applied at any stage of processing.

The following processing steps are an illustrative embodiment ofsmoothing:

-   -   a. Compute a filter kernel according to the dimensions of the        image, the kernel type and the scaling parameter, sigma;    -   b. Use the kernel to perform two dimensional symmetric        convolution with the data.

A hemoglobin calculation (950) process may be performed using the shortand long envelope images. In an embodiment, the normalized, smoothedshort and long envelope images (922, 924) are used in the hemoglobincalculation (950) process along with a 2×2 matrix of hemoglobincoefficients. The hemoglobin coefficients, referred to following as k11,k12, k21 and k22, are in proportion to the pseudo-inverse absorptioncoefficients for hemoglobin or blood. In an embodiment, the forwardabsorption coefficients may be used in the derivation of the hemoglobincoefficients and would pertain to the absorption of oxygenated anddeoxygenated blood or hemoglobin at each of the short and longwavelengths and may also account for the absorption of water and otherabsorbers. In an embodiment, the pseudo-inverse coefficients may insteadbe arrived at directly or may be empirically tuned or adjusted. In anembodiment, the pseudo-inverse absorption coefficients may also takeinto account expected values of other absorption material in the tissue.This methodology can be extended to situations where more absorbingmaterials exist or where more laser wavelengths are used. Thecomputation can also be applied for different absorbers. Thismethodology can be extended to situations where more absorbing materialsexist or where more laser wavelengths are used. As further illustratedin the Appendix, in an embodiment, the pixels of the grayscalehemoglobin map (730) may be computed on a pixel by pixel basis as(k11+k21)*short_image+(k21+k22)*long_image.

A remove common noise (930) process may be performed using the short andlong envelope images. In an embodiment, the normalized, smoothed shortand long envelope images (922, 924) are used in the remove common noise(930) process. An illustrative embodiment of a process to remove commonnoise is presented in pseudo code in the Appendix. In an embodiment, theremove common noise (930) process produces normalized, smoothed, commonnoise removed, short and long envelope images (932, 934). In anembodiment, these images (932, 934) are then used by the oxygenationcalculation (950) process along with a 2×2 matrix of oxygenationcoefficients. The oxygenation coefficients, referred to following ask11, k12, k21 and k22, are in proportion to the pseudo-inverseabsorption coefficients for hemoglobin or blood. In an embodiment, theforward absorption coefficients may be used in the derivation of thehemoglobin coefficients and would pertain to the absorption ofoxygenated and deoxygenated blood or hemoglobin at each of the short andlong wavelengths and may also account for the absorption of water andother absorbers. In an embodiment, the pseudo-inverse coefficients mayinstead be arrived at directly or may be empirically tuned or adjusted.In an embodiment, as discussed above for a hemoglobin calculationprocess, the pseudo-inverse absorption coefficients may also take intoaccount expected values of other absorption material in the tissue. Asabove, the computation can also be applied for different absorbers. Aswith the methodology for performing a hemoglobin calculation process,this methodology as well can be extended to situations where moreabsorbing materials exist or where more laser wavelengths are used. Asfurther illustrated in the Appendix, in an embodiment, the pixels of thegrayscale hemoglobin map (730) may be computed on a pixel by pixel basisas (k11+k21)*short_image/((k11+k21)*short_image+(k21+k22)*long_image).

Other methods for computing parametric maps may be used in place of themethods described above. In an embodiment, multiple laser wavelengthscan be fired at the same moment in a single frame, with the frame in itsentirety corresponding to a measurement event. The molecularconcentrations may be decoded by analyzing several measurement eventswith different combinations of fired laser wavelengths in eachmeasurement event by using Frequency-Hopping Spread Spectrum or othersimilar techniques. In an embodiment, multiple laser wavelengths can befired in a single frame, but not at the same moment, wherein molecularconcentrations can be determined by analyzing the frame using BlindSource Separation or similar techniques. The multiple wavelength singleframe approach can improve sensitivity to motion. In an embodiment, theanalyzing steps may include solving systems of absorption equations fromlaser wavelengths to determine molecular concentrations in one or moreportions of the volume.

Generate Parametric Images (240)—Denoising (735)

Returning to FIG. 7, applying a denoising (735) process may remove noisehaving characteristics similar to Gaussian white noise. In anembodiment, with the grayscale oxygenation and hemoglobin maps (725,730) created, a denoising (735) process is applied to the maps in thewavelet domain. In an embodiment, a denoising (735) process may bealternatively, or additionally, applied to real or complex sinogramsand/or real or complex images. Regardless of the subject (e.g., maps,images or sinograms), the denoising (735) process may be applied todifferent areas of processing.

In an embodiment, a multi-spectral denoising procedure may be used,which uses information from more than one optical wavelength to reducenoise. In an embodiment, multi-spectral denoising may denoise usinginformation from different sampled datasets, such as, for example, twosequential maps, images or sinograms, two non-sequential maps, images orsinograms, or from maps, images or sinograms resulting from differentwavelength light events.

In an embodiment, a denoising (735) process may operate in the twodimensional wavelet transform domain. In an embodiment, the waveletdenoising is based on a thresholding operation in the wavelet domaincoefficients. In an embodiment, a complex-valued two dimensional wavelettransform may be used. In an embodiment, wavelet thresholding via thebivariate shrinkage method may be applied for noise reduction.

The following processing steps are an illustrative embodiment ofdenoising:

-   -   a. Optionally, extend the boundaries of the image, (e.g., by        using a symmetric extension)    -   b. Compute the two dimensional wavelet transform of the image,        (e.g., a two dimensional complex dual-tree wavelet transform)    -   c. Threshold the coefficients in the wavelet domain according to        an adaptive or fixed thresholding function, the thresholding        function may be based on characteristics of the image, signal,        wavelet coefficients and/or statistical properties thereof,    -   d. Compute the inverse two dimensional wavelet transform of the        modified coefficients,    -   e. Delete any extended boundaries of the image to return an        image of the original size.

In an embodiment, the denoising (735) process will return a denoisedversion of the input, having the same dimensions as the input, such as,for example, a denoised grayscale oxygenation map or a denoisedgrayscale hemoglobin map.

Generate Parametric Images (240)—Statistical Color Mapping (740)

The statistical color mapping (740) process is performed to take agrayscale (e.g., single-image-channel (as compared with, for example, a3-image-channel RGB image)) map, and provide color to highlight databelieved to be more meaningful, and provide a transparency mask that canbe used to obscure the visibility of specific pixels. In an embodiment,the statistical color mapping (740) consists of four stages, namelycalculating statistics for the ROI, generating a color mapping,interpolating the map, and generating a transparency mask. In anembodiment, the statistical color mapping (740) consists of threestages, namely calculating statistics for the ROI, generating a colormapping and generating a transparency mask, as the stage ofinterpolating the map being optional, particularly where the map hassufficient color depth (i.e., a sufficient number of colors) to renderthe stage reasonably superfluous.

In the calculating statistics stage, statistics of the computationalregion of interest are calculated to be used as calibration or referencepoints in the color calculation. In an embodiment, the mean and thestandard deviation are calculated in this stage. As discussed above, theROI may be any shape. In an embodiment, the ROI is specified by a value,e.g., Boolean value, for each pixel in the parametric map to indicate ifthat pixel is part of the computational region of interest; thuscalculation is not limited rectangular shapes, nor even to a contiguousROI. In an embodiment, the ROI may correspond to specific pixels in theimage that meet one or more criteria, such as, e.g., pixels determinedto have at least a threshold level of hemoglobin content. The criteriafor such ROI pixels may include those criteria which may be useful forcomputation or to enhance the contrast or other aspects of the display.

In the generating a color mapping stage, a color mapping is generatedfrom the grayscale (e.g., single-image-channel) image to a predefinedcolor map. The color map determines an ordered list of colors (e.g., RGBcolors) that will be used to represent information in the output image.In an embodiment, a color reference point is initially taken as the meanof the computational ROI, plus an offset, where the offset is calculatedby the dividing the color offset bias parameter by the standarddeviation of the ROI. Then, using the statistical information, colorlimits are calculated. Color limits are numerical values of theparametric data that correspond to the first and last indices in thecolor map. Color limits may be defined in relation to the standarddeviation of the computational ROI about a computed or user-suppliedreference parameter, such as a midpoint. In an embodiment, color limitsmay be defined in relation to the standard deviation of thecomputational ROI about its mean. In an embodiment, upper and lowerlimit values are equal to the mean plus or minus the standard deviationtimes a color-contrast parameter. In an embodiment, the mapping tocolors may be achieved by relating the lower limit value to the firstvalue in the color map and the upper limit value to the last value inthe color map, and linearly mapping the intermediate values of thegrayscale image between such endpoints.

In an illustrative embodiment, the color mapping may be performed by thefollowing steps, which may be expressed in more detail in the Appendix:

-   -   a. Compute the standard deviation of the region of interest    -   b. Set the color reference point to the mean of the region of        interest plus the bias parameter divided by the standard        deviation    -   c. Set the lower color limit to the color reference point minus        the standard deviation times the color contrast parameter    -   d. Set the upper color limit to the color reference point plus        the standard deviation times the color contrast parameter    -   e. Linearly map each pixel in the grayscale image to a color        value in the color map, the lower limit value corresponding to        the first index in the color map, the upper limit value        corresponding to the last index in the color map, with values        beyond the upper and lower limits saturating at the boundary        colors, and the in-between values linearly interpolated between        the upper and lower limits.

In the (optional) interpolating step, the color map is interpolated. Inan embodiment, the color map is interpolated to smoothly map theintermediate color values and thus, prevent a choppy display. The usingthe color limits, the interpolating step rescales the parametric imageonto the color map. In an embodiment, the color of each pixel is set forintermediate values by using linear interpolation between the twocorresponding adjacent colors in the map. In an embodiment, the colormap is provided in sufficient depth so that the rescaling does notrequire interpolation, but may provide the resolution required to use adirect look-up.

The following processing steps are an illustrative embodiment of linearmapping and interpolating the color map, as expressed in more detail inthe Appendix:

-   -   a. Set maximum color map index to corresponding to the last        entry in the color map (i.e., the number of colors):        -   i. maximum_colormap_index=NumRGBColors−1    -   b. Rescale the image so that the intensities correspond to the        same numerical range as color palette for each pixel by row and        column in the parametric map        -   i.            B[row][col]=(parametric_map[row][col]−lower_color_limit_range)*(maximum_colormap_index)/(upper_color_limit_range−lower_color_limit_range)        -   ii. B[row][col]=min(max(B[row][col],0),            maximum_colormap_index)    -   c. Compute the palette indices of each pixel of B by using the        floor function and call the resulting array “index”:        -   i. index[row][col]=min(floor(B[row][col]),            maximum_colormap_index)    -   d. If the colormap has sufficient color depth, so that the        effect of the interpolation would be negligible, the RGB value        of the corresponding colormap index may be computed as        rgb_out[row][col][component]=colormap(index[row][col],        component). However, if this colormap does not have sufficient        color depth, the following steps may be performed:        -   i. Compute the remainder which is the difference between B            and index and call the resulting array “delta”:            -   1. delta[row][col]=B[row][col]−index [row][col]        -   ii. Use the value of delta to interpolate the RGB color            channels onto the provided colormap:            -   1. For each color channel component (red, green, blue),                set the color component of each pixel in                rgb_out[row][col] to:                -   a.                    rgb_out[row][col][component]=colormap(index[row][col],                    component)*(1−delta[row][col])+colormap(index+1,                    component)*delta[row][col]    -   e. Ensure that the values for the RGB colors are between 0.0 and        1.0 if the RGB values are represented by floating point values.

In the generating a transparency mask step, the transparency mask isgenerated to identify transparent portions of the map. The parameterslower_transparency_threshold and upper_transparency_threshold define thetransparency threshold based on the color limits calculated in theinterpolation step and the values present in the parametric image. In anembodiment, a parameter for opacity is used as a smoothing parameter, tosmoothly render pixels in the map rather than having a hard threshold.As shown in the Appendix, the transparency may be smoothly transitionedusing a calculate_transparency_mask subfunction. A predefined orcomputed mask may be used to make the map transparent in specificlocations. In an embodiment, a mask called display_roi (havingdimensions the same as the map) would be false (e.g., have a zero value)in locations corresponding to pixels in a map that are to be completelytransparent. In an embodiment, a pixel in display_roi is false when itfalls outside the ROI. In an embodiment, a pixel in display_roi can beset to false to obscure the corresponding data in the map, if thedisplay overlay should not be shown, such as, for example, where itfalls outside of boundary margins which may be set for edges of theimage.

In an embodiment, the output of the statistical color mapping (740)process comprises a 4 matrices that each comprise the same number ofpixels as the grayscale map, one for a values of red, green and blue(RGB), and one as an alpha channel (A) or transparency layer. Thus, inan embodiment, the statistical color mapping (740) process receives onematrix in the form of a grayscale map, and returns four, that may bereferred to collectively as a RGBA data, or a color map. Accordingly,the grayscale oxygenation map (725) is processed by statistical colormapping (740) to produce the RGBA data that collectively are referred toas the oxygenation map (250), and the grayscale hemoglobin map (730) isprocessed by statistical color mapping (740) to produce the RGBA datathat collectively are referred to as the hemoglobin map (255).

The reference names, oxygenation map and hemoglobin map are not intendedto suggest that the maps show all, or only, of the namesake material.Instead, they are being used for reference only. More specifically,although blood oxygenation is a significant tissue property displayed bythe oxygenation map, and perhaps, but not necessarily the mostsignificant tissue property displayed by the oxygenation map, it iswithin the scope of the present disclosure that the oxygenation mapdisplay no other tissue properties, and it is within the scope of thepresent disclosure that the oxygenation map display substantialadditional tissue properties. Likewise, the hemoglobin map is so namedonly for reference, and the name is not intended as a limitation on thecontent. Instead, although hemoglobin is a strong optical absorber intissue, it is within the scope of the present disclosure that thehemoglobin map display no other tissue properties, and it is within thescope of the present disclosure that the hemoglobin map displaysubstantial additional tissue properties. In other words, the names arenot intended to be limitations, however, they are believed to berepresentative of at least a substantial portion of the molecularindicators reflected in the map. In sum, the present disclosure section,as its name implies, concerns statistical color mapping as part ofgenerating parametric—or parameter-based—images. The examples showing anoxygenation map and a hemoglobin map are just provided for illustration.

Generate Parametric Images (240)—Combine Transparency Mask (750)

It has been observed that the measured optoacoustic return signal fromlocations with high hemoglobin content are the strongest. Thus, thesignal-to-noise ratio is highest in regions of high hemoglobin.Moreover, it has been observed that focusing on regions of highhemoglobin content may be diagnostically useful. Accordingly, thecombine transparency mask (750) process is designed to permit a laterdisplay of oxygenation from the regions comprising higher concentrationof hemoglobin, and thus, having a higher signal-to-noise ratio. In anembodiment, parametric maps, may be combined synergistically withinformation being presented in the combined output that is not otherwisereadily apparent or observable in the uncombined parametric maps, orobtainable from the uncombined parametric maps independently.

In an embodiment, the combine transparency mask (750) process calculatesa separate alpha channel, i.e., transparency mask, for the oxygenationdata that will constrain a specific display of the oxygenation data toregions of higher hemoglobin content, and thus to regions having highersignal-to-noise ratio. In an embodiment, the separately calculated alphachannel (A) may be combined with the RGB data in the oxygenation map(250) to form an RGBA masked oxygenation map (260).

To calculate the separate alpha channel, and thus, the transparency maskfor the oxygenation data that will constrain a specific display of theoxygenation data to regions of higher hemoglobin content, the A channel(e.g., transparency mask) from the oxygenation map (250) and thehemoglobin map (255) are combined. In an embodiment, the RGB data fromthe oxygenation map may be replicated and stored with the combinedtransparency mask. In an embodiment, when the masked oxygenation map(260) is rendered, the RGB data from the oxygenation map (250) can beaccessed.

In an embodiment, to calculate the separate alpha channel for theoxygenation data, the A channel (e.g., transparency mask) from theoxygenation map (250) and the hemoglobin map (255) may be weighted. Inan embodiment, where the alpha channel from the oxygenation map (250)and the hemoglobin map (255) are stored as real values between 0 and 1,the oxygenation map (250) and/or the hemoglobin map (255) may weightedby a positive exponent, and the two weighted masks are then multipliedtogether to produce the masked oxygenation map (260) alpha channel.Where the alpha channel from the oxygenation map (250) and thehemoglobin map (255) are stored as integer values, in an embodiment,they may be scaled prior to exponent weighting and multiplication. In anembodiment, the oxygenation map (250) and the hemoglobin map (255) alphachannel data are weighted, multiplied and then scaled.

Coregister Maps with Ultrasound (265)

The coregister maps with ultrasound (265) process coregisters theparametric oxygenation map (250), hemoglobin map (255) and/or maskedoxygenation map (260) with an acquired ultrasound image (step 215). Inan embodiment, the parametric maps being co-registered and the acquiredultrasound image are scaled to fit the desired size of the final output,and then a blended overlay with the acquired ultrasound image, based onthe alpha transparency channel of the respective parametric map. In anembodiment, the system performing processing on the optoacoustic data,and/or the system displaying the optoacoustic output—which may, but neednot be the same as the system acquiring the sinogram—would provide theoperator the ability to select a desired size of the final output.

The following processing steps are an illustrative embodiment ofcoregister maps with ultrasound, as expressed in more detail in theAppendix:

-   -   a. The RGB ultrasound_image, which may be defined by a rectangle        or other shape is interpolated or scaled to fit the        co-registered output image.    -   b. Each RGBA map (e.g., 250, 255 and/or 260) to be coregistered,        is interpolated or scaled to fit the co-registered output image.        The scaled RGBA map is overlaid on top of scaled ultrasound        image using the blending function based on the associated alpha        channel.        Method for Creating and Displaying Images

In an embodiment, the present disclosure includes a method for displayof information within the optoacoustic return signal is provided. In anembodiment, a method for the qualitative display of molecularinformation reflected by an optoacoustic return signal is provided. Inan embodiment, a method for the qualitative display of molecularinformation reflected by image statistics of an image reconstructed froman optoacoustic return signal is provided.

In an embodiment, the present disclosure includes a parametric map(a.k.a. parametric image) concerning molecular information in tissuethat is computed (as an input to or component of this approach). Becauseof the variability in the nature of how light penetrates into tissue invivo and/or due to an underdetermined set of equations from the measureddata, however, the values in the resulting parametric map are difficultto calibrate. It is thus an objective that the molecular information maybe displayed in a useful, and potentially clinically useful, qualitativefashion, based on relative values of a parametric map and/or statisticalinformation of the parametric map. In an embodiment, an ideal parametricmap may be the oxygenation saturation of hemoglobin in tissue,including, e.g., breast tissue. The purpose is to display clinicallyuseful information and compensate for underdetermined set of equationsresulting from a lack of complete information, such as, for example:having less information, or fewer lasers, than may be required toaccount for all unknowns in computation; and varying patient specificabsorption/scattering, skin/tissue properties and morphology,physiology, structures, geometry, etc.

In an embodiment, the following steps may be used to implement acomputer processing algorithm to accomplish the foregoing objective.

-   -   a. Acquiring data including a plurality of short sinograms        (205), long sinograms (210) and ultrasound images (215);    -   b. Preprocessing the sinogram data (220)    -   c. Reconstructing images from the processed sinogram data (225)    -   d. Processing the reconstructed images (230), and producing long        and short envelope images (232, 234);    -   e. Creating parametric maps;    -   f. Pre-processing of a parametric map may be done as a step        (i.e. noise-removal, smoothing, statistical normalization)    -   g. Calculating a color reference point based on statistical        information of a region of the parametric image (for example,        the mean of the region plus and adjustable bias offset).    -   h. Determining a “color range” is calculated based on        statistical information of a region of the parametric image (for        example, the standard deviation of the region).    -   i. Scaling and co-registering parametric map data onto a scaled        ultrasound or other image; and    -   j. Displaying diagnostic information concerning the tissue        examined.

Algorithms and equations useful for implementation the foregoing arediscussed above and in the Appendix.

In biological tissue, blood is a strong absorber in the NIR range. Thecalculation for oxygenation of hemoglobin in tissue may involve anormalization term in the denominator which makes the calculation lesssensitive to error. This results from the approximation thatoxy-hemoglobin and deoxy-hemoglobin (i.e., the primary optical absorbersin blood) are the full contributors to the return optoacoustic signal.From this, in an embodiment, it may be deduced that the oxygenationcalculation is sensitive to the spatially dependent fluence-ratiobetween the wavelengths, and not the spatially dependent total fluenceof each wavelength for a given point (or depth) in the tissue.

Consider, for example, a linear model of the molecular energy absorptioncontaining a (spatially dependent smooth) miscalibration term, and theresulting model of the calculated parametric image. Since the modelequation is linear (or approximately linear), the mean and standarddeviation are affected linearly by the miscalibration term in the regionof interest. Hence, a statistical method is a way to bypass themiscalibration term in a system modeled with a miscalibration term.This, in an embodiment, mean and standard deviation (and other potentialmathematical functions) when transformed by the model remain stable inrelation to the other data, and in the presence of a miscalibration.Thus, in an embodiment, even when the data is miscalibrated, (constantfluence, depth dependent fluence) the colorizations remain relativelystable.

In an embodiment, the foregoing approach can be applied with variedcalibration methods. In an embodiment, the foregoing approach may alsobe applied when other various signal processing, noise reduction, orother filters are used. In an embodiment, the foregoing approach may beused when co-registration and overlay are performed with othermodalities, such as ultrasound. In an embodiment, the foregoing approachis applicable even when varied methods, including more advanced methods,are used to calculate the parametric map. In an embodiment, theforegoing approach is applicable when the parametric map is wellcalibrated, but the unknowns such as light penetration or undeterminedequations still exist. In an embodiment, the foregoing approach isapplicable when the parametric map is well calibrated, but the unknownssuch as light penetration or undetermined equations still exist, but arecompensated for using another method, such as by estimating theunknowns; by explicitly solving for the unknowns; by solving aminimization problem to obtain the unknowns; or otherwise. In anembodiment, the foregoing approach is applicable to map quantitativeimages (i.e. a calibrated parametric map) where the reference point isfixed and not statistical. In an embodiment, the foregoing approach isapplicable to map quantitative images (i.e. a calibrated parametric map)where the color range is fixed and not statistical. As discussedelsewhere herein, the addition of another laser wavelength, in effect,reduces the number of unknowns.

In summary, the foregoing approach provides statistical color mappingand relative (i.e., qualitative) images.

In an embodiment, the present disclosure includes a method forcalibrating oxygenation or hemoglobin calculation in a dual wavelengthoptoacoustic system is provided by applying at least a plurality of thefollowing steps:

-   -   a. using reference points, or reference regions    -   b. applying calculations—as described herein, or other such        calculations that are extensions of the calculations described        herein, or as will be apparent to one of skill in the art in        view of the calculations described herein    -   c. compensating for the effect of light passing through skin        layer, coupling medium, tissue    -   d. compensating for differences in scattering, absorption;        penetration depth in a two dimensional image; a three        dimensional volume of tissue with a two dimensional cross        section from light bars, a predefined light distribution, or a        dynamically measured light distribution;    -   e. calibration from artifacts, including, differences in        artifacts from arteries or vein    -   f. applying an alternate detection scheme (automatic or manual)        to find locations of veins or arteries in advance of        calibration, which locations can be used for calculation    -   g. using co-registered ultrasound data to provide information        supplemental to the optoacoustic return signal and its        derivatives    -   h. compare the intensities in the regions or reference point at        one wavelength (for one or more types of structures/tissues)        against (at least) the regions or reference points at a second        wavelength (and potentially additional wavelength(s)) and    -   i. use the comparison to compensate for the intensity ratio        (fluence ratio) between each wavelength with respect to depth        and the absorption or scattering values of the tissue

In an embodiment, for the step of using reference points or referenceregions, such points or regions may correspond to: blood vessels;tissue; the skin layer; other known structures; depth; wavelengthspecific absorption of light through vessels (because light penetratesthrough arteries differently than through veins and hence can beidentified and discriminated in an image); or a reference point in oneor more different images. In an embodiment, the intensities in theregions or reference point at a plurality of wavelengths are comparedfor the purpose of compensating for at least one of the following: theintensity ratio (fluence ratio) between each wavelength with respect todepth (and/or position); and the absorption or scattering values of thetissue. In an embodiment the mean, standard deviation or other suchmathematical characteristic of a reference region may be used in thecalculation. In an embodiment, the characteristics of a region at onewavelength, are compared against the characteristics of a region at asecond wavelength, and furthermore compared against known absorptionparameters under presumptions of tissue composition; by fixing thepresumptions of tissue composition, the system of equations becomessolvable to compensate for the unknown fluence or fluence ratio.

In an embodiment, presumptions of tissue composition may include usingtypical ranges or values for tissue properties such as arteries, veins,vessels, background tissue, fat, muscle, or other known tissue orstructures; the properties can include optical properties, mechanicalproperties, and/or other such known properties. These presumptions canyield assumptions about the nominal optical absorption for eachwavelength. The nominal optical absorption can be useful in compensatingfor unknown fluence distribution. Thus, in an exemplary embodiment,presumptions may include that ordinary background breast tissue consistsof blood which is predominantly at approximately 80% blood-oxygensaturation, and nominal amounts of water and no other significantabsorbing molecules. In another exemplary embodiment, presumptions mayinclude that the nominal blood-oxygenation values of arteries (90%+) andveins (60% to 80%), combined with the hematocrit levels and otherphysical properties of vessels yield values for the expectedoptoacoustic return signal at each wavelength, which can be used tocalibrate for the unknown fluence distribution profile.

In an embodiment, the present disclosure includes a method forcompensation of light distribution in a clinical optoacoustic imagingsystem is provided that performs such compensation using: onedimensional curves; simulated curves; measured curves; or a region ofinterest specific method. In an embodiment, the compensation may befixed, or may be manually operated. Additional details of thecompensation method are described above.

In an embodiment, a graphical user interface (GUI) is provided foroperating a clinical optoacoustic system, the GUI including, withoutlimitation: controls that permit operator selection of a region ofinterest or operator selection of the criteria for a region of interest;and to adjust display parameters. In an embodiment, such controls mayinclude but are not limited to performing the following adjustments: thecolor contrast parameter; the selection of fluence compensation curves;the color reference point bias parameter; upper and lower colortransparency thresholds; a parameter to adjust the amount of smoothing;other compensations for absorption, filter, reconstruction, and displayparameters; and a gain parameter.

In an embodiment, a system is disclosed that does not attempt to fullydetermine the exact fluence profiles of the light as it penetrates intothe tissue. Rather a simplification, using approximative parameters forthe fluence model are used (as described above) to compensate for thelight penetration. In an embodiment, the simple parameters are initiallytuned to best approximate the light distribution for the majority ofpatients. If necessary, the parameters can be fine-tuned with auser-interface or using automatic methods. Collectively, the set ofparameters that are used to compensate for how light penetrates intotissue (whether manually or automatically produced or tuned) arereferred to as the “fluence assumptions”. In this situation it is notedthat the functional parameters displayed will be most precise incomparing the functional information of structures that are properlycompensated by the fluence assumptions. Situations where the fluenceassumptions may hold well include, without limitation:

-   -   a. where there are strong differences in oxygenation between two        compared structures with respect to the ROI;    -   b. when two compared structures are near each other and can be        assumed to have similar fluence, provided that the shadow of a        strong optical absorber does not interfere with the fluence        assumption;    -   c. when there is high contrast between the structure and the        background tissue of the ROI;    -   d. when the structures being compared have high optical        absorption;    -   e. when the presence or absence of other sources of        high-contrast structures in ROI of the functional map are        statistically common in the images which are compared;

In an embodiment, the system and method disclosed may detect relative orqualitative differences in oxygenation (or molecular concentrations)within the tissue. In an embodiment, where the displayed values are notmapped precisely in a calibrated manner on to a fixed value of bloodoxygen saturation or blood volume (which would require full knowledge ofthe fluence profile) it is nonetheless possible to display the contrastof the functional parameters within the tissue, using methods asdescribed above. In this manner, the methods and systems describedabove, are also able to produce clinically useful qualitative medicalimages. In an embodiment, the information may be displayed graphically,using color to display the quantity without presenting the operator witha numerical value corresponding to the color mapping, having a usefuldisplay of qualitative optoacoustic information, and without the directpresentation of corresponding numerical values. In an embodiment colorsare displayed in a manner that they do not need to correspond to anyparticular fixed value, but rather, the colors may adjust automaticallyto display the maximized contrast based on information contained in thecurrent image. For example, the color green need not correspond to afixed value, e.g., 80% oxygenation, but instead, may be a representationof relative or of qualitative information. In an embodiment, the methodsof fluence compensation and calibration can be used to produce moreaccurate quantitative images.

In an embodiment, the present disclosure includes an apparatus fordetecting tumors or other structures or anomalies based on functionalmorphological information, rather than merely displaying colors. In anembodiment, the present disclosure includes an apparatus forqualitatively detecting tumors or other similar structures based onfunctional morphological information, rather than merely displayingcolors.

In an embodiment, pattern classification or such techniques may beapplied to the methods of calibration, qualitative imaging or relativeimaging above. In an embodiment, a set of predetermined rules orguidelines may be used for interpretation of the images generated by theabove systems and/or method. In an embodiment, a clinical system mayinclude the rules or guidelines for the purpose of automaticallyapplying the same, or for assisting an operator to manually apply them.

Turning now to FIGS. 10, 11 and 12, and with reference to FIG. 2 aswell, four-image illustrative displays are shown. The image displayed inthe upper left is an embodiment of short envelope image (232) with aidentified rectangular region of interest. The image displayed in theupper right is an embodiment of a long envelope image (234) with thesame identified rectangular region of interest. The image displayed inthe lower left is an ultrasound image (295) also showing the identifiedrectangular region of interest. The image in the lower left is oneembodiment of a display of coregistered ultrasound image and oxygenationmap (275). On the right hand column of the four-image display are thevalue for various illustrative parameters that, in an embodiment, can beoperator selected.

Turning now to FIGS. 13, 14 and 15, and with reference to FIG. 2 aswell, six-image illustrative displays are shown. The top left is anultrasound image (295), the bottom left and center are embodiments ofshort and long envelope images (270, 290). The top center image is anembodiment of a display of a coregistered ultrasound image andoxygenation map (275), the top right image is an embodiment of a displayof a coregistered ultrasound image and hemoglobin map (280), and thebottom right image is an embodiment of a display of a coregisteredultrasound image and masked oxygenation map (285).

In an embodiment, colorization on an image shows relative oxygenation,thus, for example, red may mean an area is less oxygenated than thesurrounding tissue and green may mean it's more oxygenated. In anembodiment, molecular optical contrast provides differentiation betweenhypoxic blood of breast carcinomas (which may be shown in red) andnormally oxygenated blood in benign masses (which may be shown ingreen).

Optoacoustic System and Method

Returning to FIG. 1, generally, device 100 provides an optoacousticsystem that may also be employed as multimodality, combined optoacousticand ultrasound system. In an embodiment, the device 100 includes a probe102 connected via a light path 132 and an electrical path 108 to asystem chassis 101. Within the system chassis 101 is housed a lightsubsystem 129 and a computing subsystem 128. The computing subsystem 128includes one or more computing components for ultrasound control andanalysis and optoacoustic control and analysis; these components may beseparate, or integrated. In an embodiment, the computing subsystemcomprises a relay system 110, an optoacoustic processing and overlaysystem 140 and an ultrasound instrument 150.

In an embodiment, the light system 129 is capable of producing pulses oflight of at least two different wavelengths. In an embodiment, the lightsystem 129 outputs should be capable of producing short pulses of lightin each of those wavelengths, e.g., a pulse lasting less than about 100ns, and potentially as short as about 5 ns. As will be apparent to oneof ordinary skill in the art from this disclosure, the inventionsdisclosed herein may also be practiced using pulsed light comprisingpulses lasting greater than 100 ns. In an embodiment, the light source129 includes two separate lights 130, 131. The output of the lightsystem 129 is delivered to the probe 102 via the optical path 132. In anembodiment, the lights 130, 131 are lasers producing light in theinfrared, near-infrared, and/or visible spectrum. In an embodiment,light 130 and light 131 each produce light at a different wavelength inthe infrared or near-infrared spectrum. In an embodiment, the opticalpath 132 used to deliver light from the light source 129 to the probe102 is a fiber optic bundle comprising multiple strands of opticalfiber. In an embodiment, the optical path 132 comprises sufficientoptical fibers of sufficient size (diameter) to carry a short, highpowered pulse of light to the distal end of the optical path 132. In anembodiment, the total pulse energy carried over the optical path 132 maybe on the order of one or more millijoules. In an embodiment, the totalenergy per light pulse delivered from the optical path 132 is less thanabout 100 millijoules. In an embodiment, the total energy per lightpulse carried over the optical path 132 is in the range of about 10-30millijoules, and the optical path 132 comprises between about 1,000 and2,000 optical fibers of between about 100 and 300 microns each. In anembodiment, a single fiber can be used as the optical path. In suchembodiment, the fiber may be 1000-1500 microns in diameter. Of course,the diameter of such single fiber may be smaller, e.g., 400 microns.Given the required total pulse energy carried over the fiber, oneskilled in the art can calculate the diameter required of the fiberaccordingly.

In an illustrative embodiment, the light system 129 may use Nd:YAG andAlexandrite lasers as its two lights 130, 131, although other types orwavelengths, and additional lights, may also be used. Lights 130, 131should be capable of producing a short pulse of light, e.g., a pulselasting less than about 100 ns, and more preferably around 5 ns. In anembodiment, the two lights 130, 131 can be separately triggered. In anembodiment, the light output by the lights 130, 131 may be projectedonto the same light path 132 through the use of an optical element 133that generally permits one light 130 to pass through from a first sideto a second side, while reflecting one light 131 that strikes the secondside. The use of optical element 133 or a similar element permits thealignment of the output of two lights 130, 131 such as lasers ontoproximal end of the light path 132. In an embodiment, optical elements133 can align the light output from more than two lasers, for example,through the use of multiple optical elements 133. In an embodiment,multiple light systems and light paths may be employed, with the lightof each light system being carried on separate fibers or fiber groupsthat may be intermingled and/or randomized (discussed further below)and/or grouped at their distal ends. Intermingled, as used in thiscontext, refers to the mapping of the fibers in the light path such thatfibers are generally distributed in a relatively even manner in thedistal groupings. Thus, a plurality of adjacent fibers on the proximalend of the light path would generally be about evenly divided ingroupings on the distal end. As an illustrative example, where there aretwo distal groupings, any arbitrary selection of a sufficient group ofadjacent fibers on the proximal end should be about evenly split betweenthe two distal groupings. The randomization, intermingling and/orgrouping need not take place at any specific location on the light path132. In other words, for example, the division of a fiber cable from oneproximal group to two distal groups can occur at any point along thelight path 132, or along substantially the entire length of the lightpath 132. Similarly, the randomization and/or intermingling need nottake place along the entire length of the light path, but rather, forexample, may take along a the distance of, e.g., a few centimeters ormore near either end of the light path, or anywhere else along the lightpath 132. Randomizing fibers between one end and the other end of alight path prevents a local anomaly affecting an adjacent group of thefibers on the input from affecting an significant adjacent group of thefibers on the output. Intermingling fibers between one end and the otherend of a light path prevents a local anomaly affecting an adjacent groupof the fibers on the input from disproportionately affecting one groupor subgroup of fibers on the output.

Where the light path terminates in multiple groupings (or subgroupings)of fibers, the distal ends of the groupings (or subgroupings) may befused, or lapped and polished, or just secured together (removably orotherwise). In an embodiment, the distal end of the light path is formedinto a plurality of groups that are spaced in such a manner so as topermit light to emit on each side of the transducer array. In anembodiment, the distal end of the light path is formed into a pluralityof groups that are spaced in such a manner so as to permit light to emitaround the entire transducer array. In an embodiment, the distal end ofthe light path is formed into two or more groups, and the two or moregroups subdivided into subgroups that are separately secured by a lightbar guide, which light bar guide may be associated with the group. In anembodiment, optical elements 133 can consist of optical elements thatare used to measure the light energy to determine energy per lightpulse.

Although the total energy per light pulse carried over the optical pathis in the order of tens of millijoules, because the pulse of lights 130,131 is so short, the peak power output over the optical path 132 isfrequently approaching or in the megawatt range. Accordingly, the outputof lights 130, 131 has the capacity to cause the optical fibers and/orthe cladding on the optical fibers to burn, discolor or otherwisedegrade. Such degraded optical fibers and/or cladding, whether burnt,discolored, or otherwise, can exacerbate the problem as they begin totransmit less light power and cause more heating. Accordingly, in anembodiment, sufficient number and size optical fibers are present in theoptical path 132 to permit handling of the peak power loads and avoidfiber burnout. To accommodate higher peak power, a larger fiber bundlecan be used. It will be apparent to a person of skill in the art thatthe peak power capacity of a fiber bundle can be increased by increasingthe number of optical fibers, or the diameter of optical fibers, orboth. Notably, however, as the dimension of the fiber bundle increases,the weight and flexibility of the optical path 132 may become lessdesirable. Moreover, when using more optical fibers, or optical fibersof a larger diameter, the output of light source 129 must be deliveredto the optical path 132 across the wider diameter of the larger bundle.In an embodiment, regardless of the ultimate size of the proximal end oflight path 132, the output of light source 129 should be distributedsufficiently across its cross section to prevent burn out failures whenoperating in expected peak power ranges.

In an embodiment, the fibers of the proximal end of the light path 132may be fused to form a fused entry point to the optical path 132 for theoutput of light source 129. In an embodiment, the fiber ends can befused by applying heat. In an embodiment a fused end may be surroundedwith a metal ring. In an embodiment a fused end may be surrounded with astainless steel ring. Once the proximal end of optical path 132 has beenfused, it will resist burnout at substantially higher peak power. Forexample, using a fused end light path 132 may permit carriage of three,four or even five times as much peak power. The ability to carrysubstantially higher peak power in a given optical path 132 permits useof a more flexible and lighter fiber optic bundle to carry the same peakpower as an un-fused optical path 132. Thus, in an embodiment, where a½″ fiber optic bundle may have been required in an un-fused bundle ofoptical fibers forming an optical path, a ¼″ fiber optic bundle with afused proximal end may be used to carry the same peak power. A ¼″ fiberoptic bundle with a fused proximal end is approximately ¼ of the weightand much more flexible than a ½″ fiber optic bundle. Moreover, fusing ofthe proximal end of light path 132 may produce an even smaller fusedarea to illuminate using light source 132 as the fusing removes theinter-fiber spaces that would have existed in the bundled end of theround-cross-section optical fibers. Accordingly, one or more of thefollowing advantages may be attained by fusing the proximal end of theoptical fibers comprising the light path 132: reduced weight of thelight path; increased flexibility of the light path; reduced failure;increased reliability; higher peak power capacity.

In an embodiment, the proximal end of the light path 132 may beseparated into separate groups for separate lights 130, 131 in a lightsource 132, and light output by the lights 130, 131 may be projectedonto different proximal groups of the light path 132. More than twoseparate lights may be used, and the proximal end of the light path 132may be separated into at least one group for each light. Each group offibers at the proximal end of the light path 132 may be fused togetherto form a fused entry point to the optical path 132 for the light withwhich it is associated. In an embodiment, the fibers of a light pathhaving multiple groups on the proximal and are intermingled with respectto the groups or subgroups on the proximal ends. In an embodiment, thefibers of a light path having multiple groups on the proximal and arerandomized with respect to the groups or subgroups on the proximal ends.In an embodiment, a light path is provided with a fused proximal end(input) and at least two groups on its distal end (outputs), the fibersbeing intermingled and randomized, thus preventing a local anomalyaffecting adjacent fibers at the input of the light path from: (i)causing an anomaly affecting a substantial number of adjacent fibers onan output; and (ii) disproportionately affecting one of the outputs. Inan embodiment, a light path is provided with at least two groups on itsproximal end (inputs) and at least two groups on its distal end(outputs), the fibers being intermingled and randomized, thus preventinga local anomaly affecting adjacent fibers at an input of the light pathfrom: (i) causing an anomaly affecting a substantial number of adjacentfibers on an output; and (ii) disproportionately affecting one of theoutputs. In an embodiment, a light path is provided with at least twofused groups on its proximal end (inputs) and at least two fused groupson its distal end (outputs), the fibers being intermingled andrandomized, thus preventing a local anomaly affecting adjacent fibers atan input of the light path from: (i) causing an anomaly affecting asubstantial number of adjacent fibers on an output; and (ii)disproportionately affecting one of the outputs.

In an embodiment, optical fiber of the type that may be used in lightpath 132 includes a transparent core surrounded by a transparentcladding material with a lower index of refraction. The core may be madefrom any transparent material, although excellent results have beenobserved using pure glass (i.e., silica). In an embodiment where abundle of optical fibers are to be fused, the cladding may be removed inthe area to be fused. In an embodiment, the cladding may be removedusing a chemical process. For example, for some cladding, hot sulfuricacid or acetone may be used. The removal of cladding prior to fusingreduces the chance of particles of the cladding material becomingembedded in the fused end, as such particles may interfere with thelight transmission across light path 132.

In an embodiment, the light output by the lights 130, 131 is senttowards a fused optical fiber bundle at the proximal end of light path132 via an optical path, which may include optical element 133, internalto the light source 129. In an embodiment, light source 129 is a lasersystem capable of outputting laser light pulses, at one or a morewavelengths, onto light path 132. In an embodiment, light path 132 is afiber optic bundle having a fused end proximal to the light source 129.

In an embodiment, the device 100 also comprises an electrical path 108running to and/or from the probe 102 to the system chassis 101. In anembodiment, electrical path 108 runs to and/or from the probe 102 to arelay system 110 within the system chassis 101. The electrical path 108may run near, alongside or coaxially with the optical path 132 from theprobe 102 toward their respective connections on the system chassis 101.In an embodiment, the electrical path 108 comprises a plurality ofseparate coaxial wires. In an embodiment, the electrical path 108 is runin a common jacket with at least a portion of the optical path 132.Running electrical path 108 in a common jacket with at least a portionof the optical path 132 reduces the number of cables running from thesystem chassis 101 to the probe 102. Running electrical path 108 in acommon jacket with at least a portion of the optical path 132 mayminimize the diameter and weight of, and increase the durability of, thecombined cables (i.e., optical path 132 and electrical path 108) runningfrom the system chassis 101 to the probe 102.

In an embodiment, the plurality of coaxial wires is woven around atleast a portion of the optical path 132. As discussed above, manyconsiderations go into the number of separate optical fibers used inoptical path 132. As discussed further below, numerous designconsiderations go into the number of separate electrical leads or tracesforming the electrical path 108. In an embodiment, there are about 256leads (corresponding to 256 transducers) forming the electrical path 108and approximately 1,000 separate optical fibers forming the optical path132, making the fiber:lead ratio about 4:1. As will be apparent, it ispossible to commingle the optical fibers and leads or traces in theelectrical path in a variety of ways, including, for example, bundling agroup of individual fibers with a single electrical lead or trace, orbundling proportionally larger groupings of fibers and leads together.In an embodiment, the bundling of fibers and leads or traces would bedone generally in the proportion of fibers:leads in the system.

One or more displays 112, 114, which may be touch screen displays, areprovided for displaying images and all or portions of the device 100user interface. One or more other user input devices (not shown) such asa keyboard, mouse and various other input devices (e.g., dials andswitches) may be provided for receiving input from an operator. As anoption, power and control signal lines 109 carry power to the probe 102and control signals between the probe 102 and the computing subsystem128.

In an embodiment, the connections between the probe 102 and the systemchassis 101 may be formed into a flexible cable, which may consist ofthe light path 132, the control line(s) 109 and the electrical path 108.The flexible cable may be covered in a common outer jacket or sheath forconvenience and ease of use. In an embodiment, a medial portion of thelight path 132 forms the core of the single flexible cable, and medialportions of the electrical path 108 and/or control line(s) 109, if any,may be wrapped or braided about the medial portion of the light path132. In an embodiment, a common outer jacket or sheathing encloses afiber optic bundle forming a medial portion of the light path 132, acoaxial bundle forming a medial portion of the electrical path 108, andcontrol line(s) 109, if any. In an embodiment, the fibers forming amedial portion of the light path, and the wires forming a medial portionof the electrical path 108, as well as control line(s) 109, if any, maybe intertwined or intermingled with each other along the medial portionof the connections between the probe 102 and the system chassis 101.

In an embodiment, the distal end of the flexible cable(s) connecting theprobe 102 and the system chassis 101 is associated with, andnon-removably integrated as part of the probe 102. In an alternativeembodiment, the distal end of the flexible cable(s) connecting the probe102 and the system chassis 101 is removably associated with the probe102. To removably associate the flexible cable(s) connecting the probe102 and the system chassis 101 requires both optical fiber connectionfor the light path 102 and electrical connection for the electrical path108 and control line(s) 109, if any.

In an embodiment, the light path 132 is split into two sections, and thetwo sections are brought together using an optical fiber connector inclose proximity to the probe 102. The optical fiber connector may bephysically located within the probe 102, or may span opening 404 (seeFIG. 4), or be located outside the probe 102. In an embodiment, anoptical fiber connector would mechanically couple and align the cores ofthe fibers making up the light path 132 so that light can pass from onesection to the other without significant loss. In an embodiment, thefacing ends of the two sections of the light path 132 are fused, and maybe first stripped of cladding and then fused, to mitigate issues of corealignment. Regardless of whether the fiber ends are fused, the endsinternal to light path 132 that are being connected by the optical fiberconnector may be lapped and polished to improve light transmission. Inan embodiment, probe 102 has a removable access panel that permitsaccess to optical and/or electrical connectors located within the probe.

To support removability of the electrical path 108 and control line(s)109, if any, removable electrical connectors may be provided. In anembodiment, flex circuit is elongated so that connectors 314 which areconnected to the end of electrical path 108 are accessible from aremovable access panel, thereby permitting the disconnection ofelectrical path 108. In an embodiment, electrical path 108 (and controlpath 109, if any) is split into two sections, and the two sections arebrought together using an electrical connector in close proximity to theprobe 102. The electrical connector may be physically located within theprobe 102, or may span opening 404 (see FIG. 4), or be located outsidethe probe 102. In an embodiment, an electrical connector wouldelectrically couple the two portions of the electrical path 108 so thatsignals can pass from one section to the other without significant loss.

In an embodiment, the signals carried on the probe-side portion ofelectrical path 108 are analog signals, and are terminated into ananalog-to-digital converter, and the signals carried on the otherportion of the electrical path—the portion that connects to the systemchassis 101—are digitized representations of the analog signals carriedon the probe-side portion of the electrical path 108. In an embodiment,the signals carried on the electrical path 108 are digital signals giventhat the analog-to-digital conversion is performed in the body of theprobe handle

In an embodiment, the probe-side optical connector(s) and electricalconnector(s) for the flexible cable(s) that operationally connects thesystem chassis 101 to the probe 102 are integrated into a singleconnector that can be operated to quickly disconnect the probe 102 fromthe cable.

Turning now to FIG. 16, the probe 102 includes an array of ultrasoundtransducer elements forming an ultrasound transducer (not shown) coveredby an acoustic lens 1605. In an embodiment the ultrasound transducercomprises an array of piezoelectric elements that can both transmit andreceive acoustic energy. In an embodiment, at least some of theultrasound transducer elements are capable of detecting ultrasoundfrequencies over a wide range. For example, ultrasound transducerelements may be capable of detecting ultrasound in the range from about50 KHz to 20 MHz. This range can be achieved by applying a highimpedance load (e.g., in the range of 5,000 to 50,000 ohms) to achieve alower frequency response. The ultrasound transducer elements are capableof generating electrical energy in response to receiving ultrasoundacoustic energy. The electrical energy generated by the ultrasoundtransducer elements receiving ultrasound is transmitted to the computingsubsystem 128 via electrical path 108.

The probe 102 also includes one or more optical windows 1603 throughwhich the light carried on optical path 132 can be transmitted to thesurface of a three-dimensional volume 160. In an embodiment, it isdesirable to locate one side of the optical window 1603 as close aspractical to the acoustic lens 1605. The total area of an optical window1603 is important to maximize energy for a given fluence incident on thesurface of the volume 160.

In an embodiment, the multiple strands of optical fiber making up theoptical path 132 are terminated in two light bars (not shown). In anembodiment, the ultrasound transducer elements (not shown) are arrangedin an array that runs along a geometric plane and are generally spacedequidistant from each other. In an embodiment, the light bars (notshown) are oriented longitudinally, on each side of the planar array ofultrasound transducer elements. Preferably the ultrasound transducerelements generate electrical energy in response to both ultrasoundacoustic energy received in response to stimulation caused by the pulsedlight sources 130, 131 (i.e., the optoacoustic return signal) and toultrasound acoustic energy received in response to acoustic output ofthe ultrasound transducer elements.

Referring back to FIG. 1, in use, the probe 102 may be placed in closeproximity with organic tissue, phantom or other three-dimensional volume160 that may have one or more localized inhomogenities 161, 162, such ase.g., a tumor, within. An ultrasound gel (not shown) or other materialmay be used to improve acoustic coupling between the probe 102 and thesurface of the volume 160. The probe 102, when in proximity with thesurface of the volume 160, can emit a pulse of a light through theoptical windows 1603 or an ultrasound through acoustic lens 1605, andthen generate electrical energy corresponding to ultrasound detected inresponse to the emitted light or sound.

In an embodiment, the computing subsystem 128 can trigger activity fromlight system 129 over control signal line 106. In an alternativeembodiment, the light system 129 can create the trigger signal andinform the computing subsystem 128 of its activity over control signalline 106. Such information can be used to by the computing subsystem 128to begin the data acquisition process. In this respect, it is noted thatcommunication over control signal line 106 can flow both ways betweenthe computing subsystem 128 (and/or the optoacoustic processing andoverlay system 140 therein) and the light system 129.

In an embodiment, computing subsystem 128 can utilize control signalline 106 to control the start time and duration of light pulses fromeach light source 130, 131. The computing subsystem 128 can also triggerthe probe 102 to emit ultrasound acoustic energy via the ultrasoundtransducer elements behind the acoustic lens 1605.

In an embodiment, the computing subsystem 128 receives electricalsignals representative of the ultrasound detected by the ultrasoundtransducer elements, in response to an ultrasound transmitted signal oran optically generated ultrasound signal, behind the acoustic lens 1605via electrical path 108. In an embodiment, the electrical signalrepresentative of the ultrasound detected by the ultrasound transducerelements behind the acoustic lens 1605 is the analog electrical signalcreated by the elements themselves. In such embodiment, the electricalsignals representative of the ultrasound detected by the ultrasoundtransducer elements behind the acoustic lens 1605 is transmitted to thecomputing subsystem via electrical path 108, and electrical path 108 isselectively directed by relay system 110 to the optoacoustic processingand overlay system 140 or the ultrasound instrument 150 for processingof the detected ultrasound. In such embodiment, the ultrasoundinstrument 150 can receive the same input (over the same connector) asit would receive from an ultrasound probe.

In another embodiment, the electrical signal representative of theultrasound detected by the ultrasound transducer elements behind theacoustic lens 1605 is digitized by an analog-to-digital converter whichcan be housed in the probe 102. In such embodiment, time-resolvedelectrical signal representative of the ultrasound detected by theultrasound transducer elements behind the acoustic lens 1605 istransmitted across the electrical path 108. Where the electrical signalis digitized at the probe 102, as will be apparent to one of skill inthe art, the relay system 110 may be implemented to deliver digital datato the optoacoustic processing and overlay system 140 or the ultrasoundinstrument 150, or may not be needed at all.

The signal representative of the ultrasound detected by each of theplurality of ultrasound transducer elements behind the acoustic lens1605 may be carried on a separate wire over the electrical path 108.Alternatively, the signal representative of the ultrasound detected by aplurality of ultrasound transducer elements behind the acoustic lens1605, or even all of the ultrasound transducer elements behind theacoustic lens 1605, may be multiplexed (e.g., time division or frequencydivision) utilizing a multiplexer in the probe and a demultiplexer inthe computing subsystem 128.

In an embodiment, the ultrasound instrument 150 processesultrasound-induced acoustic signals to produce ultrasound images and theoptoacoustic processing and overlay system 140 processes light-inducedacoustic signals to produce optoacoustic images. In an embodiment, theultrasound instrument 150 and optoacoustic processing and overlay system140 can be combined into an integrated system performing the combinedfunctions of both. As discussed above, in an embodiment, electricalsignals representative of ultrasound detected by the probe 102 anddelivered to the computing subsystem 128 via electrical path 108 isswitched between the ultrasound instrument 150 and the optoacousticinstrument 140 via relay system 110 in accordance with whether thesignal results from ultrasound stimulation or light stimulation.

In an embodiment, tomographic images reflecting theultrasound-stimulated data may be generated by the ultrasound instrument150 and tomographic images reflecting the light-stimulated data may begenerated by the optoacoustic processing and overlay system 140.

Images, including tomographic images, produced by the optoacousticprocessing and overlay system 140 can be stored in a computer memory inthat system, along with data associated with sequence or time and dateof the image data that was captured. Images, including tomographicimages, produced by the ultrasound instrument 150 may be transmitted tothe optoacoustic processing and overlay system 140 via a suitableinterface 170, where they can be stored, along with images generatedfrom the light-stimulated data, in a time-synchronized manner. In anembodiment, images stored in the memory of the optoacoustic processingand overlay system 140 can be recorded to another memory, e.g., anon-volatile memory internal to, or external to, the device.

In an embodiment, the optoacoustic processing and overlay system 140 canoverlay images produced by the ultrasound instrument with imagesproduced by optoacoustic instrument 140 for storage in the memory and/ordisplay on one or more monitors 112, 114. In an embodiment, theoverlayed optoacoustic image may be shown in a distinct color todistinguish it from the ultrasound image. In an embodiment, the overlaidoptoacoustic image may contain colors that correspond to detailsdiscernable through optoacoustic imaging, such as, for example, bloodoxygenation. In an embodiment, oxygenated blood is shown more in redthan blue, while deoxygenated blood is shown in more blue than red. Asused herein, the expression overlaid includes merging of the image bymixing as well as traditional overlaying of the image.

In an embodiment, the device 100 may be configured to operate in a cyclecomprising a sequence of successively generating and acquiring datarelating to one of the device's modalities, i.e., ultrasound oroptoacoustic. The minimum time spacing between operation of the device'smodalities depends on the device 100 components and their ability tofully execute and recycle for use. In an embodiment, a user can selectbetween a variety of preprogrammed cycles such as, for example:ultrasound only; wavelength one only; wavelength two only; wavelengthone and two (which may be caused, e.g., by separate lasers, or by asingle, quickly tunable, laser); multiple iterations of wavelength oneand two followed by ultrasound; and/or multiple iterations of ultrasoundfollowed by wavelength one and/or two. Other and further combinationswill be apparent to one of skill in the art. Moreover, where the device100 is capable of generating more than two wavelengths, numerousadditional preprogrammed cycles may be desirable. In an embodiment,additional cycles can be added by the machine operator. In anembodiment, the data collection of an entire cycle is generally intendedto be directed to substantially the same portion of volume 160 and to beaccomplished in rapid succession. In an embodiment, the device 100cycles are normally in the range of 1 to 50 per second, and moretypically in the range of 2 to 20 per second, as discussed above. Themaximum cycle frequency is limited only by the capabilities of the cycleand modalities.

In an embodiment, the displays 112, 114 of device 100 can be configuredto show various information depending upon the selected operatingcycles. In an embodiment, any display 112, 144 or portion of the displaycan show at least one of the following: an ultrasound only image; afirst wavelength response only image; a second wavelength response onlyimage; a combined first and second wavelength response image; and/or anoverlay ultrasound image and a wavelength response or combinedwavelength response image. The combined first and second wavelengthimage may comprise a differential or other combinatorial means toprovide the image. In an embodiment, an image can be displayedcorresponding to each of the separate data collections in a cycle, orcorresponding to the sum or difference between any or all of them.

In an embodiment, the device can be operated using a three-phase datacollection operation, one phase generating and collecting data inresponse to ultrasound stimulus, one phase generating and collectingdata in response to a first wavelength of light, and one phasegenerating and collecting data in response to a second wavelength oflight. In an embodiment having a light source capable of generating morethan two wavelengths, the device can be operated using a multi-phasedata collection operation, one phase generating and collecting data inresponse to ultrasound stimulus, and one phase generating and collectingdata in response to each wavelength of light. Other and furthercombinations will be apparent to one of skill in the art.

Using proper wavelength(s), optoacoustics is effective in identifyingblood within a volume 160, and using multiple wavelengths can be used toreadily distinguish between oxygenated and deoxygenated blood.Similarly, using proper wavelengths, optoacoustics is effective formeasuring localized hemoglobin content within a volume 160. Thus, forexample, a malignant tumor, which is characterized by increased bloodconcentration and decreased oxygenation, will appear very differently inan optoacoustic image than a benign growth, which is not characterizedby such an increased blood concentration and has more normaloxygenation. Moreover, specific wavelengths of light can be selected tobetter distinguish between various biological tissues and organs. Whilea large spectrum of infrared, near-infrared and visible wavelengths canproduce optoacoustic response in biological entities, oxygenated bloodis more optoacoustically responsive than deoxygenated blood to a lightsource having a wavelength of about 1064 nm, while deoxygenated blood ismore optoacoustically responsive than oxygenated blood to a light sourcehaving a wavelength of about 757 nm. The number and specificwavelength(s) of light used in the device 100 are selected in accordancewith the makeup of the volume and the type of target that is ofinterest.

In an embodiment employing an ND:Yag laser to emit a pulse of lighthaving a predominant wavelength of about 1064 nm and employing anAlexandrite laser to emit a pulse of light having a predominantwavelength of about 575 nm, the ND:Yag laser will be pulsed first,followed by a delay of about 50 milliseconds, followed by the pulsing ofthe Alexandrite laser. The cycle length before the following pulse ofthe ND:Yag laser may be 100 milliseconds or more. Thus, in anembodiment, the pulses/delays may be as follows: ND:Yag pulse, 50millisecond delay, Alexandrite pulse, 50 millisecond delay, yielding afrequency of about 10 Hz, and a cycle time of about 100 milliseconds.Generally, regardless of the total cycle time, the time between thefirst and second light events should be as short as reasonablypractical. Thus, in another embodiment, the pulses/delays may be asfollows: ND:Yag pulse, 50 millisecond delay, Alexandrite pulse, 150millisecond delay, yielding a frequency of about 5 Hz, and a cycle timeof about 200 milliseconds. In yet another embodiment, the pulses/delaysmay be as follows: ND:Yag pulse, 50 millisecond delay, Alexandritepulse, 250 millisecond delay, or a 450 millisecond delay, or a 950millisecond delay, yielding, respectively, a frequency of about 3.33, 2and 1 Hz, and cycle times of about 300, 500 and 1,000 milliseconds. Inan embodiment, the Alexandrite laser may be pulsed before the ND:Yag. Inan embodiment, a graphical user interface (GUI) is provided foroperating a clinical optoacoustic system, the GUI including, withoutlimitation: controls that permit operator selection of the cycle timeand/or the order of light source pulsing.

FIG. 17 shows an exploded view of an embodiment of the probe 102 shownin FIG. 16. Shells 1702, 1704 are separated to show the componentswithin the probe 102. The shells 1702, 1704 may be made from plastic orany other suitable material. The surfaces of the shells 1702, 1704 thatmay be exposed to light, and especially light generated by the lightsubsystem 129, are preferably both reflective (i.e., light colored)material and light scattering (i.e., having a scattering coefficientbetween 1 and 10). In an embodiment, the surfaces of the shells 1702,1704 are highly reflective, i.e., more than 75% reflective. In anembodiment, the surfaces of the shells 1702, 1704 are very highlyreflective, i.e., more than about 90% reflective. In an embodiment, thesurfaces of the shells 1702, 1704 have low optical absorption, i.e.,less than 25% absorptive. In an embodiment, the surfaces of the shells1702, 1704 have very low optical absorption, i.e., less than about 10%absorptive. In addition, the material forming the shells 1702, 1704should be acoustically absorbent to absorb, rather than reflect ortransmit acoustic energy. In an embodiment, white plastic shells 1702,1704 are used.

In an embodiment, flex circuit 1712 comprises a plurality of electricaltraces (not shown) connecting cable connectors 1714 to an array ofpiezoelectric ultrasound transducer elements (not shown) formingultrasound transducer 1710. In an embodiment, flex circuit 1712 isfolded and wrapped around a backing 1711, and may be secured theretousing a bonding agent such as silicon. In an embodiment, a block 1713 isaffixed to the backing 1711 opposite the array of piezoelectricultrasound transducer elements. In an embodiment, the ultrasoundtransducer 1710 comprises at least 128 transducer elements, although itmay be desirable to have a greater number of transducer elements, asadditional elements may reduce distortion, and/or increase resolution,accuracy and/or depth of imaging of the device 100. The cable connectors1714 operatively connect the electrical traces, and thus, the ultrasoundtransducer 1710, to the electrical path 108. In an embodiment, theelectrical path 108 includes a coaxial wire for each ultrasoundtransducer element in the ultrasound transducer array 1710.

The ultrasound transducer 1710 fits within housing 1716 so that thetransducer elements are in close proximity to, or in contact with anacoustic lens 1605. The acoustic lens 1605 may comprise a siliconrubber, such as a room temperature vulcanization (RTV) silicon rubber.In an embodiment, the housing 1716 and the acoustic lens 1605 are formedas a single unit, from the same RTV silicon rubber material. In anembodiment, the ultrasound transducer 1710, portions of the flex circuit1712, backing 1711 and block 1713 are secured within the housing 1716including an acoustic lens 1605 using a suitable adhesive such assilicon to form a transducer assembly 1715. The block 1713 can be usedto affix or secure the transducer assembly 1715 to other components.

To whiten, and reduce the optoacoustic effect of light generated by thelight subsystem 129 on an RTV silicon rubber acoustic lens 1605 and/orthe transducer assembly 1715, in an embodiment, the RTV silicon rubberforming the acoustic lens 1605 and/or the transducer assembly 1715 maybe doped with TiO₂. In an embodiment, the RTV silicon rubber forming theacoustic lens 1605 and/or the transducer assembly 1715 may be doped withapproximately 4% TiO₂. In an embodiment, the outer surface of theacoustic lens 1605 and/or the outer surface of the transducer assembly1715 may additionally be, or alternatively be, coated with a thin layerof metal such as brass, aluminum, copper or gold. Gold, however, hasbeen found to have a tendency to flake or crack off of RTV siliconrubber. In an embodiment, the RTV silicon may be first coated withperylene, then coated with nickel, then coated with gold, and finally,again, coated with perylene. In an embodiment, the RTV silicon may befirst coated with nickel, then coated with perylene, then coated withgold, and finally, again, coated with perylene. In an embodiment, theoutermost coating of perylene may be omitted. The multiple layeringprovides a durable gold coating without any substantial adverse effectto the acoustic properties of the acoustic lens 1605, and without anysubstantial adverse effect to the transducer assembly 1715 to detectultrasound. In practice, it has been found that the perylene coatingsadjacent to the nickel and the gold layers, may curl at the edges ratherthan adhering well to the metals or rubber upon which it is deposited.Thus, as discussed in more detail below, in an embodiment, the portionsof the acoustic lens 1603 and/or transducer assembly 1715 having an edgecapable of being mechanically secured against other components toprevent curling or peeling. In an embodiment, substantially the entireouter surface of the transducer assembly 1715, including the acousticlens 1605, are coated with continuous layers of nickel, then perylene,then gold and then perylene again.

In an embodiment, a reflective material surrounds the transducerassembly 1715 from the rear edge of the housing 1716 to the end of theflex circuit 1712 to reflect any light from the light path 132 that maybe incident upon its surfaces. In an embodiment, an electromagneticshield for RF energy surrounds the transducer assembly 1715 from therear edge of the housing 1716 to the end of the flex circuit 1712. In anembodiment, the lights 130, 131, may draw substantial energy (e.g., morethan 1,000 volts for a few nanoseconds) creating substantialelectromagnetic RF energy in the area of the probe 102. In anembodiment, the transducer assembly 1715 from the rear edge of thehousing 1716 to the end of the flex circuit 1712 is surrounded by afoil, which may act as a reflective material and an RF energy shield. Inan embodiment, the foil is selected from the group: copper, gold,silver. In an embodiment, the foil is tied into the device's 100electrical ground.

Spacers 1720 space and position the light bar guide 1722 with respect tothe transducer assembly 1715. Spacers are preferably made from materialsthat reduce its optoacoustic response to light generated by the lightsubsystem 129. In an embodiment, the spacers 1720 are made from amaterial similar to the light contacting portions of the shells 1702,1704. In an embodiment, the light bar guide 1722 encases optical fibersthat are part of the light path 132. In an embodiment, the opticalfibers making up the light path 132 may be randomly (or pseudo-randomly)distributed throughout the light bar guide 1722, thus making specificlocations on the light receiving end of the fiber optic bundle at leastpseudo-random with respect to corresponding specific locations on thelight emitting end of the optical fibers retained by the light bar guide1722. As used herein the term randomly (or pseudo-randomly) distributedoptical fibers making up the light path 132 means that the mapping offibers from the proximal end to the distal end is done such that alocalized interference in the light path 132 (e.g., burnout of a groupof adjacent optical fibers) or a localized phenomenon (e.g., non-uniformlight at the entry point to the optical path 132) will have an effect onthe overall power transmitted, but will not have an operationallysignificant effect on any specific part of the distal end of the lightpath 132. Thus, two optical fibers adjacent at the proximal end areunlikely to be adjacent at the distal end of the optical path 132. Whereoptical fiber bundles are fused at the proximal and distal ends, therandomization must be done before at least one end is fused. As usedherein the term randomly (or pseudo-randomly) distributed optical fibersdoes not mean that two different optical paths 132—i.e., for differentdevices 100—must differ from each other. In other words, a single“random” mapping may be reproduced in the light path of differentdevices 100 while still meeting the criteria of being a randomized.Because light generally behaves in a Gaussian manner, the entry point tothe light path 132 is typically less than perfectly uniform.Randomization, as discussed above, may accommodate for the non-uniformentry of light into the light path 132. Randomization may also providehomogenization of light fluence over area illuminated, as it may aid inmore evenly distributing the light fluence.

In an embodiment, the optical fibers encased by a light bar guide 1722all end on substantially the same geometric surface, e.g., a curved orflat plane. In an embodiment, the fibers at the distal end, within agiven light bar, may be grouped and subgrouped in a manner that may helphold the fibers in position during manufacturing. Such grouping (such asin groups for the two light bars) and subgroupings (e.g., havingsubgroups per lightbar) may further the even distributing over thegeometric surface. Any number of subgroups may be used. In anembodiment, the number of subgroups is selected to be practical forfabrication and manufacturing. In an embodiment, the number of subgroupsis selected to facilitate the manufacturing process. In an embodiment,the number of subgroups may be between 5 and 20, and may be 15. In anembodiment, the fiber groups are formed by placing fiber subgroupsbetween physical channels that are molded or machined into light barguide 1722, or its internal and/or external surfaces.

In one embodiment, after the fibers have been attached to the light barguide 1722, the fiber ends may be lapped and polished to provide for amore uniform angle of light emission. In an embodiment, the light barguide 1722, as installed in the assembled probe 102, directs the lightemitting there-from at an angle slightly less than normal to the distalface of the probe 102, and specifically, at small angle inwards, towardsthe plane normal to and intersecting the center of the acoustictransducer array 1710. In an embodiment, the distal end(s) of theoptical path 132 should match—or closely approximate the shape of theacoustic transducer array 132.

The term bar, as used in “light bar guide” herein is not intended toimport a specific shape. For example, the light bar guide 1722 may guidethe distal ends of optical fibers into substantially any shape such as,without limitation, a whole or part of a circle, oval, triangle, square,rectangle or any irregular shape.

In an embodiment, one or more light bar guides 1722 and optical windows1603 are external to the shells 1702, 1704 housing the acoustictransducer assembly 1715, and are adapted to be attached to the outersides of one or more of the shells 1702, 1704.

In an embodiment, the angle of light emitting from the optical window1603 may be adjustable. In an embodiment, the light emitting from theoptical window 1603 may be adjustable across a range. At one end of therange, light may emit from the optical window 1603 in a direction normalto the distal face of the probe 102, and at the other end of the rangelight may emit from the optical window 1603 at an inward angle of up to45 degrees or more towards the plane normal to and intersecting thecenter of the acoustic transducer array 1710. The range can be smalleror larger.

In an embodiment wherein a probe has two optical windows 1603, the angleof light emitting from both optical windows 1603 can be adjustable,individually, or together. Where adjusting the angle of light emittingfrom both optical windows 1603 together, the light direction would, ineach case increase or decrease the angle of inward projection, that is,projection towards the plane normal to and intersecting the center ofthe acoustic transducer array 1710. In this manner, a larger lightfluence can be directed deeper into the volume 160 (by angling towardnormal), or shallower (by angling more inwardly).

Controlling the direction of the light angle can be done by moving thelight guide 1722, or it can be accomplished optically through the use ofpost-light path 132 optics. Optical solutions may include the use of oneor more lenses and/or prisms to re-direct the light that has beentransmitted through the light path 132, or by using an optical elementhaving a variable index of refraction, such as, for example, an opticalelement having an index of refraction controlled in response to electricfields. Re-directed light can be directed to illuminate a desired area,such as an area directly beneath the transducer elements 1710.Controlling the direction of light transmitted by the probe 102 isuseful to maintain safe and optimize the direction of the light withrespect to the skin and the transducers.

Control line 109 may be used to send commands redirecting light and/orto report the actual direction of light at the time a light pulse isemitted from the light path 132. The angle of the light emitting fromthe optical window 1603 may be important data to consider wheninterpreting acoustic information resulting from the light pulse.

In an embodiment, the device 100 can adjust the angle of incident laserlight emitting from the probe 102. Adjustment of the angle of incidentlaser light emitting from the probe 102 may be carried out under thecontrol of commands which may be sent via control line 109, or may bemanually carried out. In an embodiment, a standoff may be used, e.g., tohelp direct incident laser light to the desired depth, or closer to thesurface than can be achieved without a standoff. In an embodiment, thestandoff is relatively transparent to both acoustic and light, andpreferably to acoustics in the ultrasound range and light one or more ofthe wavelengths utilized by the light source 129. While the use ofstandoffs is known in ultrasound applications to aid in imaging ofobjects close to the surface of the volume 160 because ultrasoundresolution lacks the capability to detect objects at a nominal distancefrom its transducers, the use of a standoff in the present applicationis for a different purpose, namely, to allow the light sources to beaimed directly under the transducer elements 1710. In an embodiment, thestandoff is separate from the probe 102, and placed between the volume160, and the distal end of the probe 102 comprising the acoustic lens1605 and one or more optical windows 1603. In an embodiment, thestandoff may be integral to the probe, and may be move into place andwithdrawn as desired.

Optical windows 1603 may also be part of the probe 102 assembly. In anembodiment, the optical windows 1603 is spaced from the end of the lightbar guide 1722, and thus, from the ends of the optical fibers making upthe light path 132. The term optical window, as used here, is notlimited to mechanically or optically flat optical matter, or solely totransparent optical matter. Instead, the term is used to refer to anoptical element that may or may not effect light passing there-through,but will permit at least a substantial portion of the light incident onthe side of the window proximal to the light path 132 to exit the probeassembly 102 in a manner that is dependent on the properties of theoptical element. In an embodiment, the optical window 1603 may betransparent, which permits transmission of light, and specifically lightemitted from the end of the light path 132, to volume 160 when thedistal end of the probe 102 is in contact with or close proximity tothat volume 160. In an embodiment, the optical window 1603 may betranslucent, permitting diffusion and transmission of light, andspecifically light emitted from the end of the light path 132, to volume160 when the distal end of the probe 102 is in contact with or closeproximity to that volume 160. In an embodiment, the optical window 1603may be a lens, permitting the shaping and directing of light, andspecifically light emitted from the end of the light path 132, to volume160 when the distal end of the probe 102 is in contact with or closeproximity to that volume 160.

In the assembled probe 102, one edge of the optical window 1603 is inclose proximity to, or in contact with, the transducer assembly 1715.The proximity of the optical window 1603 to the transducer assembly 1715allows light emitted from the optical window 1603 to be emitted from alocation close to the acoustic lens 1605, and thus close to the plane ofthe transducer array 1710.

In use, a coupling agent (e.g., gel) may be used to improve the acousticcontact between the distal end of probe 102 and the volume 160. If thecoupling agent makes contact with the distal end of the optical fibersforming the light path 132, extraneous acoustic signal may be generatedin response to light transmission over the light path 132. In anembodiment, the distal end of the probe 102, including optical window1603, mitigates the potential acoustic effect of a coupling agent inresponse to light emitting from the light path 132 by creating a gapbetween the coupling agent and the distal end of the optical fibers.

FIG. 18 shows a cutaway view taken along the centerline of the widerface of one embodiment of an assembled probe 102 such as the probe shownin FIG. 16. Shells 1702, 1704 support optical windows 1603 andtransducer assembly 1715 at the distal end of the probe 102. Spacers1720 supported by transducer assembly 1715 and shells 1702, 1704 aid inthe positioning of optical widows 1603 and light bar guides 1722, and inmaintaining gap 1802 between light bar guides 1722 and the opticalwindows 1603.

The distal ends of the optical fibers making up the light path 132 maybe positioned such that they do not create a physical sound conductionpath to the volume 160 or to the acoustic transducers 1710. In anembodiment, the gap 1802 serves the purpose of preventing high frequencysound conduction path between the distal ends of the optical fibersmaking up the light path 132 and the volume 160 or the acoustictransducers 1710. Specially selected materials, as discussed below, canbe used to ensure that the light bar guide 1722 reduces and/or minimizesthe physical sound conduction path between the distal end of the lightpath 132 and the volume 160 or the acoustic transducers 1710.

Flex circuit 1712, with piezoelectric transducer elements (not shown)thereon, wraps around backing 1711, and electrically connects thepiezoelectric transducer elements with the cable connectors 1714 at eachend of the flex circuit.

Opening 1804 in the shells 1702, 1704 provides an opening for opticalpath 132 (FIG. 1), electrical path 108 (FIG. 1) and optional power andcontrol lines 109 (FIG. 1) to enter the inside of the probe 102. In anembodiment, a rubber grommet (not shown) may be used to providestability and strain relief to the paths or lines passing into the probe102 through opening 1804.

Turning to FIG. 19A, a typical pattern of light striking a surface inclose proximity to the ends of ten optical fibers is shown. Today,typical, reasonably flexible optical fibers have a diameter in the rangeof about 50 to 200 microns. Light exiting an optical fiber tends toexpand slowly, see, for example, an illustrative example of lightexpanding after leaving the end of an optical fiber in FIG. 19B. Therate of expansion of the light beam leaving an optical fiber is afunction of the diameter of the optical fiber and the refraction indexof the optical fiber material, and may also be a function of therefraction index of the material to which the fiber is connected. When agroup of optical fibers are placed in close proximity to a surface to beilluminated, a light pattern like that seen in FIG. 19A results.

In an embodiment, optical fibers having smaller diameters are employedto broaden the illuminated area and minimize weight and increaseflexibility of the light path 132. Light diverges as it exits a fiberoptic, and its divergence as it exits is inversely related to thediameter of the fiber—in other words, light diverges faster out ofsmaller diameter fiber optics. Thus, for example, optical fibers in therange of under 50 microns, and potentially less than 30 microns may bedesirable to broaden the illuminated area, thus reducing, or potentiallyeliminating the need for a beam expander. In an embodiment, the distalend of one or more groups of the optical fibers comprising the lightpath 132 may be fused to avoid the characteristic pattern of light shownin FIG. 19A.

In an embodiment, an optoacoustic probe should produce a relativelyuniform light distribution incident upon the surface of the illuminatedvolume. It may also be desirable for an optoacoustic probe to produce arelatively large area of light distribution. Providing a relativelylarge and uniform light distribution permits an optoacoustic probe todeliver a maximum amount of energy without exceeding a specific lightfluence on any given area of the illuminated surface, which can maximizepatient safety and/or improve the signal-to-noise ratio. For thesereasons, it is not desirable to locate the optical fiber ends in tooclose proximity with the surface of the illuminated volume, and thus,obtain a small or uneven light distribution such as the one seen in FIG.19A.

In an embodiment, the optical fibers may be moved away from the surfaceof a volume to be illuminated. Moving the end of the optical fibers awayfrom the surface of the volume to be illuminated will cause the beamsemitted from each optical fiber to expand, and produce a more uniformarea of light distribution. One potential issue associated with movingthe optical fibers away from the surface of the volume to beilluminated, is the optoacoustic effects caused by stray portions of theexpanding beam. Another potential issue is the effect of enlarging thedistance (between the end of the optical fibers and the surface to beilluminated) on the shape or size of a probe. Further, increasing thenumber of optical fibers (and thus enlarging the area of the fiberbundle emitting light) will increase the cost, weight and flexibility ofthe optical path 132 (FIG. 1), and may also affect the size of theprobe.

Because the probe 102 is designed to be handheld, it is desirable tokeep the probe head (the wider, distal portion of the probe 102) shortso that the probe stem (the narrower, proximal portion of the probe 102)is relatively close to the surface of volume 160. Additionally, becausethe probe 102 is designed to be handheld, its total thickness is also aconsideration for comfort, convenience and operational effectiveness.Accordingly, locating the distal ends of the fibers forming light path132 at a sufficient distance from the optical window 1603 to permitexpansion to fill the optical windows 1603 with uniform light fluence isnot preferred. Similarly, using a very large number of fibers to enlargethe area of the fiber bundle held by the light bar guide 1722 at thedistal end of the light path 132 and thereby attempting to permitexpansion to fill the optical windows 1603 with uniform light fluence isalso not preferred as it would, among other things cause undue weight,inflexibility, size and cost. Moreover, reducing the size of the opticalwindow 1603 would reduce the total potential safe energy output of thedevice, and thus, is not preferred.

Turning to FIGS. 20B and 20C, in an embodiment, a beam expander 2001 b,2001 c may be used to expand the beam of light, causing it to becomemore uniform over a shorter distance. FIG. 20b shows the use of a groundor frosted glass beam expander 2001 b, while FIG. 20C shows the use of alens beam expander 2001 c. In an embodiment, where the light bar guide1722 is generally rectangular, a lens beam expander 2001 c may be acylindrical convex lens or a cylindrical concave lens. In an embodiment,a convex lens (not shown) may be used as a beam expander. It will beapparent to one of skill in the art that other lenses, lens systems orother optical systems or combinations thereof, can be used to spread andmore evenly distribute the light.

Referring back to FIG. 18, in an embodiment, the light bar guides 1722are angled inward toward the ultrasonic imaging plane on the endretaining the distal ends of the fibers. The inward angling of thedistal end of the light bar guide 1722 permits the light emittingthere-from to better fill, and thus, evenly illuminate the opticalwindow 1603. Gap 1802, which may include a beam expander, may providespace for the light transmitted across the light path 132 to expand tofill the optical window 1603. The inward angling tends to cause thedirection of the light incident on the surface of the volume 160 tostrike the surface at an angle less than normal, and thus, potentially,to better propagate into the volume beneath the acoustic lens 1605covering the ultrasound transducers 1710.

Turning back to FIG. 1, because the probe 102 is intended for handhelduse, the weight and flexibility of the light path 132, the electricalpath 108 and the optional power and control lines 109 is ofconsideration. In an embodiment, to make the light path 132 lighter andmore flexible, the light path 132 is constructed from as few fibers aspossible. A limiting factor to how few a number of fibers that can beused, is the amount of light carried across the optical path 132. Thetransmission of too much light over a fiber will damage the fiber. Thelight path 132 must carry the total amount of light that will be fluenton the surface of the volume 160, plus any light lost (e.g., absorbed orscattered) between the light source 129 and the surface of the volume160 illuminated. Since the maximum area of illumination is known not toexceed the size of the optical window 1603, and because the area ofillumination is subject to fluence limits per unit area, a total lightenergy carried by the light path 132 can be approximated by multiplyingthe fluence limit by the size of the optical windows 1603. The FDAprovides numbers for the human safe level of fluence.

The volume 160 illuminated generally has its own optoacoustic response,which is especially apparent where light fluence is greatest, namely, atthe surface of the volume 160. Increasing the area of illumination ontothe surface of the volume 160 (e.g., by increasing the size of theoptical window 1603 and beam) reduces the optoacoustic affect generatedby the surface of the volume 160 itself, and thus may reduce theundesirable optoacoustic signal generated by the surface of the volume160 itself as compared to a desired signal representing theinhomogenities 161, 162.

In addition to unwanted optoacoustic signal generated by the surface ofthe volume 160 itself, there may be other sources of unwantedoptoacoustic signals that can be detected by the ultrasound transducer,such as the side walls surrounding the space between the optical windows1605 and the respective light bar guides 1722, the acoustic lens 1605and portions of the transducer housing 1716. The optical windows 1603and any optional beam expander 2001B, 2001C may also be sources ofunwanted optoacoustic signals that can be detected by the ultrasoundtransducer.

In an embodiment, the walls surrounding the space between the opticalwindows 1605 and the respective light bar guides 1722 may be made from amaterial that has high acoustic absorption properties and/or that iswhite and/or has high light scattering and/or reflecting properties.Using materials having these characteristics may reduce unwantedoptoacoustic signals that can be detected by the ultrasound transducer.In an embodiment, the spacers 1722 can be made from a resin materialsuch as Micro-Mark CR-600, a two part high performance casting resinthat dries to a white color.

In an embodiment, a layer (not shown) of material that has high acousticabsorption properties and/or that is white and/or has high lightscattering properties is placed between the transducer assembly 1715 andthe light bar guides 1722 in the assembled probe 102. Alternatively, thelayer may be applied directly to the transducer assembly 1715 or thelight bar guide 1722 where the two parts contact in the assembled probe102. This layer may reduce unwanted optoacoustic signals that can bedetected by the ultrasound transducer. In an embodiment, the layer canbe made from a resin material such as Micro-Mark CR-600, a two part highperformance casting resin that dries to a white color. In an embodiment,the layer (not shown) may also comprise a reflective coating. In anembodiment a reflective coating of gold is applied to the layer toreflect light that might otherwise strike the layer.

In an embodiment, anti-reflective coatings may be used to reduce theoptoacoustic signature of the optical window 1603 and/or the beamexpander 2001B, 2001C. In an embodiment, magnesium fluoride may be usedas an anti-reflective coating on the optical window 1603 and/or the beamexpander 2001B, 2001C. Anti-reflective coatings may be used to reduceand/or minimize energy absorbed or reflected by the optical window 1603.

In an embodiment, the optoacoustic signature of the transducer assembly1715 and/or acoustic lens 1605 can be reduced by whitening. In anembodiment, an acoustic lens 1605 comprising RTV silicon rubber may bewhitened and have its optoacoustic signature reduced by being doped withabout 4% TiO₂. It is believed that the TiO₂ doping increases thereflectivity of the acoustic lens and therefore the absorption, and alsohas a scattering effect that tends to diffuse the optoacoustic responseof the RTV silicon rubber, bringing the response down to a lowerfrequency which can be more easily filtered. As discussed above, theouter surface of the transducer assembly 1715 and/or acoustic lens 1605may be given a metal coating, such as gold, copper, aluminum or brass.In an embodiment, the metal coating, and in particular, gold, reducesthe optoacoustic signature of the transducer assembly 1715 and/oracoustic lens 1605. It is believed that gold reduces the optoacousticsignature of the acoustic lens 1605 because of its high reflectivity inthe light spectrum. In an embodiment, the acoustic lens may not bewhitened and may retain its natural color, or be colored differently tominimize optical absorption at one or more particular wavelengths. In anembodiment, the acoustic lens may be made of materials other than RTVsilicon rubber, such as, for example, buna-N rubber (i.e., nitrilerubber) or latex rubber.

As discussed above, the optical fibers at the end of the optical path132 are retained by the light bar guide 1722 with all of the fiber endsretained by the light bar guide 1722 located on substantially the sameplane. In an embodiment, the fiber ends may be fixed in place usingmechanical force, an adhesive, or a combination of mechanical force andan adhesive. The fibers may be glued near their distal end to keep themin the desired location and pattern, and/or to reduce output ofmechanical energy due to laser firing. In an embodiment, the spacesbetween optical fibers fixed within the light bar guide 1722 may befilled with a material having one or more of the followingcharacteristics: sound absorbing, light scattering, white and/or lightreflecting. In an embodiment, the optical fibers, which may be encasedby a light bar guide 1722 at the distal end of the light path 132 arefused. Fusing fibers at the distal end of the light path 132 may permitthe light emitting from the light path to be more uniform.

In an embodiment, a reflective coating is placed on areas of the shells1702, 1704 where laser light emanating from the optical path 132 maystrike it, including with the assembled probe, and in the areas designedto make skin contact, e.g., near the optical window 1603 and otherportions of the distal end of the probe 102. In an embodiment, theshells 1702, 1704 are coated in gold where laser light emanating fromthe optical path 132 may, or is likely to strike it. In an embodiment,portions of the shell 1702, 1704 may be made from gold, although atpresent this may be cost prohibitive.

In an embodiment, a proximity detector system (not shown) is used todetermine that the distal end of the probe 102 is on or very near thesurface of a volume. Among the reasons such a proximity detector systemis desirable is that it can be used to prevent pulsing of the lightsource 129 when the probe 102 is not in close proximity to a volume 160under inspection, or to be inspected. This may be a safety issue as thelight source 129 may produce light at levels that can be harmful, e.g.,to the eyes. The proximity detector system may be implemented in theform of: a mechanical contact switch at the distal end of the probe; anoptical switch looking at reflections of a non-harmful beam from thesurface of the volume 160; a conductive switch that is closed by contactwith the volume 160 and/or any acoustic gel or other materials betweenthe volume 160 and the distal end of the probe; a conductive switch anda standoff comprising a conductive surface for contact with the distalend of the probe 102; a conductive switch and a thin, optically andacoustically transparent, conductive surface applied to the surface ofthe volume 160 of interest; an acoustic transducer switch that candetect close proximity of the volume 160 by transmitting and looking forthe reflection of a sound within a specific time; an acoustic transducerswitch that can detect close proximity of the volume 160 by using anarrow shape sound transmitter and receiver and using the reflection todetect proximity; using one or more of the transducers in the transducerarray as a proximity detector by looking for a signal return; or byoperating the device 100 in an ultrasound mode and looking for anultrasound image.

In an embodiment, an optical detector (not shown) may be located in theprobe 102 to take a measurement from which output energy can beestimated or deduced. In an embodiment, the optical detector willmeasure reflected energy such as energy reflected by the beam expanderor optical window. In an embodiment, the optical detector will measurescattered energy such as energy scattered by the materials surroundingthe gap 1802. The measurement of the optical detector can be transmittedto the system chassis 101 via control signal line 109, where it can beanalyzed to deduce or estimate the light output of the probe 102. In anembodiment, control functionality in the system chassis 101 can controlor regulate the light output of the light system 129, and thus the lightoutput of the probe 102 based on a measurement made by the opticaldetector. In an embodiment, control functionality in the system chassis101 can control or regulate the gain in the transducer receivers tocompensate for variation of the light output of the probe 102 based on ameasurement made by the optical detector. In an embodiment, thecomputing subsystem 128 can trigger differing activity from light system129 over control signal line 106 based on a measurement made by theoptical detector. In an embodiment, a measurement made by the opticaldetector can be used to control for variations in the electrical systemor the power to the device 101. Similarly, in an embodiment, ameasurement made by the optical detector can be used to control forvariations in the optical path 132 or other optical elements of thedevice 100. In an embodiment, the optical detector can be used to causethe fluence of light output by the probe 102 to remain close to, butbelow, safe limits by accommodating for variations in electrical oroptical characteristics that might otherwise cause the fluence of lightoutput by the probe 102 to exceed or fall far below the safe limit.

In an embodiment, a safety feature would prevent disconnection of theprobe 102 from the flexible cable when the system is in operation (e.g.when the laser is firing). To implement this safety feature, in anembodiment, the system 100 can use control line(s) 109 to operate amechanical lock on the connector between the probe and the flexibleconnector. In an embodiment, a fail-secure mechanical lock would onlypermit disconnection of the probe 102 from the flexible cable when aspecific control line(s) 109 was at voltage greater than a prespecifiedamount.

As discussed above, the device 100 comprises a probe 102 that, in anembodiment, is capable of transmitting both ultrasound and light to avolume 160, and is capable of receiving and processing an ultrasonicresponse to the transmitted ultrasound and light. The ultrasonicresponse to the transmitted ultrasound is typically a narrow bandwidtharound the transmit frequency, with a percent bandwidth of about 70% andhaving no meaningful response below 2 Mhz, while the ultrasonic responseto transmitted light is typically in a much broader range, such as therange of about 50 KHz to 20 MHz or more, typically centered in the rangeof 6 MHz to 8 MHz. In an embodiment, ultrasound is transmitted andreceived by the transducers 1710, while light is transmitted by a light130, 131, across the optical path 132, and across the optical window1603 or other aperture, the ultrasonic response thereto is received byseparate transducers (not shown) tuned to receive the higher frequencyrange typically generated by the optoacoustic effect. The separatetransducers are operated with high impedance amplifiers, e.g., having animpedance of more than 200 ohms, and preferably being about 500 ohms ormore. Where the optoacoustic response is received by separatetransducers, or by the same transducers using differing impedance loadsfrom their use for ultrasound response, the signals representing theultrasound response may be carried back to the system chassis 101 onseparate wires of the electrical path 108 from the signals representingoptoacoustic response.

In an embodiment, ultrasound is transmitted by the transducers 1710, andthe ultrasonic response thereto is received by the transducers 1710, andlight is transmitted by a light 130, 131, across the optical path 132,and out the optical window 1603, and the ultrasonic response thereto isalso received by the transducers 1710. In such embodiment, thetransducers 1710 are operated with high impedance amplifiers having animpedance of more than 1K ohm and less than about 100K ohms, and morepreferably between 2K and 10K ohms input impedance. In an illustrativeembodiment, the transducers 1710 may be operated with a 5K ohms inputimpedance amplifier.

In an embodiment where the probe 102 is equipped with ultrasoundtransducers 1710 and separate transducers (not shown) tuned to receivethe higher (vs. broader) frequency range typically generated by theoptoacoustic effect, the optoacoustic response for light thattransmitted by a light 130, 131, across the optical path 132, and outthe optical window 1603, may be received by both the transducers 1710and by the separate transducers. Using both sets of transducers toreceive ultrasound responsive to the optoacoustic effect may captureadditional data that can be used to better analyze target 161, 162within a volume 160.

Turning to FIGS. 21-23, phantoms formed from plastisol are useful forregistration and calibration. FIG. 21 shows a phantom 2100 for use inconnection with an optoacoustic imaging device and/or a multimodalultrasound and optoacoustic imaging device. The phantom 2100 comprisesseveral targets 2102, 2104, 2106. In an embodiment, the targets 2102,2104, 2106 are dissimilar, one being particularly responsive to a firststimuli but not a second, one being particularly responsive to a secondstimuli but not the first, and one being particularly responsive to boththe first and second stimuli. In an embodiment, the first stimuli may bean optoacoustic pulse at a first wavelength and the second stimuli maybe an optoacoustic pulse at a second wavelength. In an embodiment, thefirst stimuli may be a traditional ultrasound signal and the secondstimuli may be an optoacoustic pulse at one or more wavelengths. To makematerials responsive to the various stimuli, doping is generally used.For optoacoustic response, material is doped with an absorber at therelevant frequency or frequencies. For ultrasound response, material isdoped to be denser. Using phantom 2100 the response to the first orsecond stimuli can be demonstrated and or calibrated in response to thedegree to which 2102, 2104, and/or 2106 targets are doped. This allowsthe determination of the doping percentages at which it is difficult todifferentiate between target responses.

FIG. 23 shows a phantom 2300 for use in connection with an optoacousticimaging device and/or a multimodal ultrasound and optoacoustic imagingdevice. The phantom 2300 comprises several targets 2302, 2302 embeddedin plastisol. In an embodiment, the targets 2302, 2304 are generallylinear and similar. In an embodiment, the targets 2302, 2304 are naturalor synthetic horsehair. Using phantom 2300 multiple modalities such asoptoacoustics and ultrasound can be co-registered. In an embodiment, amultimodality probe is coupled to the phantom, and an image showing theoutput of each modality is presented on the screen overlaid upon oneanother. Using a joystick or other input device, an operator canmanually co-register the images, thus providing co-registration for themultimodality probe. In an embodiment, the images of each of themodalities are compared by a computer, and automatically co-registered.

FIG. 22 shows an active phantom 2200 for use in connection with anoptoacoustic imaging device and/or a multimodal ultrasound andoptoacoustic imaging device. The phantom 2200 comprises an active target2212 embedded in plastisol and target control 2201. In an embodiment,active target 2212 comprises a linear array of transducers 2210 on abacking 2211; the transducers 2210 are operatively connected to targetcontrol 2201 through the body of the active target 2212, connector 2214and by electrical path 2208. Target control 2201 can create signals thatdrive the transducers 2210. In an embodiment, target control 801selectively creates signals to output a known ultrasound pattern and/orsimulates an optoacoustic return signal. Using phantom 2200 permitstesting and calibration of the optoacoustic return signal receiving andprocessing portions of an optoacoustic device 100 without concern forthe integrity of the light output system.

As discussed above and shown in the Figures discussed above, the probe102 may have a linear array of transducers 1710 that are adapted toreceive the optoacoustic return signal through an acoustic lens 1605.Other transducer geometries are also desirable. Turning to FIGS. 24A-C,in various embodiments, a linear transducer array may be oriented withsides that protrude at angles from the plane of the central portion ofthe array, or may be in the general shape of an ellipse or asemi-circle. Turning to FIGS. 25A-C, in various embodiments, atransducer array may be provided in a two dimensional shape as generallyillustrated. Although the illustrations show only small numbers oftransducers, e.g., 7 per line, in practice, many more transducers wouldbe used. As discussed above, in an embodiment, 128 or more transducersper line, may be used. For example, in FIG. 25A, an illustrative arrayis shown comprising four generally linear arrays of transducers alignedon simple Cartesian coordinates in asterisk-type configuration andssharing a common center transducer. In FIG. 25B, an illustrative arrayis shown comprising three generally linear arrays of transducers whereinthe transducers are arranged similarly distant from one another onconcentric rings in the various arrays, and also arranged inasterisk-type configuration and sharing a common center transducer. InFIG. 25C, an illustrative array is shown comprising three generallylinear arrays of transducers arranged in a simple grid.

With respect to each of numerous geometries shown, to develop an imagefrom the optoacoustic return signal requires (i) that the transducersare coupled to the volume 160 containing the target(s) of interest whenused to detect an optoacoustic return signal, and (ii) that the detectedoptoacoustic return signal is processed using information relating therelative position of the transducers to each other in space. Transducersmay be use in a flexible array that adapts to the shape of the volume160 when coupled therewith, provided that the relative position of thetransducers to each other in space is known, and used in processing theoptoacoustic return signal.

In an embodiment, an optoacoustic probe can be used to detect theoptoacoustic return signal by sampling the transducers for a period oftime after the optoacoustic inducement, such as a laser, has beendeployed. In an embodiment, at least some of the desired content of theoptoacoustic return signal is in the frequency range of about 100 KHz to12 MHz. Thus the optoacoustic return signal may be sampled at 30 MHz,which is a sufficient sampling rate for at least some of the desiredcontent of the signal. In an embodiment, the sampling apparatus iscapable of sampling up to 256 channels at 65 MHz. In an embodiment, anoptoacoustic probe may have 128 or 256 transducers, and may be sampledat or around 30 MHz.

In an embodiment, an optoacoustic probe can detect the optoacousticreturn signal by sweeping through multiple transducer elements orthrough multiple groups of transducer elements. For example turning toFIG. 25A, the 25 shown illustrated transducer elements are shown in fourgroups 2510, 2515, 2520, 2525 of seven, noting that each group shares acommon center element. In an embodiment, after an optoacoustic pulsesuch as from a laser, a first cycle of the detection of the optoacousticreturn signal can be conducted first through one group 2510, then asecond group 2515, then a third group 2520, and then a fourth group2525. Once that first cycle of the detection of the optoacoustic returnsignal is complete, a second cycle, a third cycle and so on maycontinue. The sampling apparatus discussed in an embodiment abovecapable of sampling up to 256 channels 65 MHz is also capable ofsampling two separate arrays of 256 transducers at 30 MHz, or fourarrays of 128 transducers at 30 MHz. Accordingly, in an embodiment asshown in FIGS. 25A-C, a sampling apparatus may be used to sweep throughtwo or more groups of overlapping (e.g., FIGS. 25A-B) or unique (e.g.,FIG. 25C) transducers and thus sample the optoacoustic return signal inresponse to a single optoacoustic event, such as the firing of a singlelaser pulse.

As will be apparent to one of skill in the art, sampling apparatus arecapable of sampling at rates higher than the illustrative one discussedabove. Using sampling apparatus that can sample more channels or atfaster rates would permit a larger number of total samples to begenerated in response to a single optoacoustic event. Accordingly, it iswithin the scope of this specification and the inventions disclosedherein, to use larger groups, and/or more groups, of transducers thanare illustrated above, to be swept through in response to a singleoptoacoustic event.

Advantages exist in connection with each of the differing transducergeometries discussed above. The straight linear array is compact, costefficient, easily handled, and is the most commonly used in standardultrasound B-mode imaging. The curved or winged linear arrays mayconform better to the irradiated volume, and thus, provide bettercoupling. The non-linear(multiple row, also known as 1.5 dimensional)arrays permit additional angles from which to resolve the optical returnsignal from a given voxel, which may improve resolution and/or addclarity and contrast to the image and/or may better supportthree-dimensional imaging applications. Flexible arrays may also providebetter coupling with the volume. The non-linear arrays can allowtransducer elements that are optimized for ultrasound to co-exist withtransducer elements that are optimized for optoacoustics within the sameprobe. Different transducer elements are used to create either the US orOA images.

An optoacoustic return signal can be generally acquired within a windowof less than about 100 microseconds. Using a generally acceptedapproximation for the speed of sound in tissue of around 1,500 m/s, a100 microsecond acquisition window may correspond to a depth of up toabout 15 centimeters. In an embodiment, an optoacoustic return signalcan be acquired within a window of about 65 microseconds, and containinformation from as deep as about 10 centimeters. In an embodiment, thefrequency of light events is anticipated to be generally on the order ofevery 50 to 100 milliseconds (0.05 to 0.1 seconds). Accordingly, thedata acquisition may occur less than 1% of the time, and closer tobetween 0.1% or 0.2% of the time, leaving more than 99% of the timewhere no data acquisition is occurring. Electrical noise may be createdby powering the light subsystem 129 and/or other components of thesystem 100. Accordingly, in an embodiment, to prevent electrical noisefrom affecting the data acquisition, a synchronization is utilized toprevent powering unnecessary components during that period, leavingpower only to the preamps, analog-to-digital converters and multiplexer.In an embodiment, the synchronization between power and data acquisitionallows for the power system to be optimally electrically quiet duringthe acquisition time period. In an embodiment, this may be achieved bypowering down noisy digital components during this period or allowingcharged capacitors to power the acquisition hardware at this time. In anembodiment, this is triggered by the same trigger that starts theacquisition cycle and is controlled by the master processor to controlthe turning on/off of the peripheral components not involved with theacquisition cycle. In an embodiment, this takes from a few nanosecondsto a few microseconds. In an embodiment, the same synchronization signalcan be used to synchronize one or more of the other switching powersupplies within and/or associated with the OA system. By controlling oneor more such switching power supply, electrical noise produced by thepower supply (e.g., switching transients) can be caused to occur at thesame time. In an embodiment, by using a synchronization signal,electrical noise produced by the power supplies in the OA system can bepurposefully staggered, leaving temporal windows of electrical quietduring which data may be acquired.

As discussed above, in an embodiment, the same transducers are used toreceive acoustic-generated ultrasound and to receive the optoacousticreturn signal. The geometry of acoustic-generated ultrasound transducersis not optimal for receiving the optoacoustic return signal.Accordingly, in an embodiment, separate transducers are used for theacoustic-generated ultrasound and the optoacoustic return signal. Theacoustic-generated ultrasound transducers can have a narrower bandbecause the transducer itself sends the signal that it needs to detect.The optoacoustic return signal transducer can have a wider band, suchas, for example, 50 KHz to 20 MHz. This wider band is preferred, amongother reasons, because gain falls faster with depth on the optoacousticreturn signal. Thus, in an embodiment, a plurality of transducers isused to receive the acoustic-generated ultrasound and a separateplurality of transducers is used to receive the optoacoustic returnsignal. In an embodiment the plurality of transducers used to receivethe acoustic-generated ultrasound and the separate plurality oftransducers used to receive the optoacoustic return signal compriseapproximately the same number of transducers. In an embodiment theplurality of transducers used to receive the acoustic-generatedultrasound and the separate plurality of transducers used to receive theoptoacoustic return signal each comprise at least 128 transducers, andmore preferably, would comprise at least 192 transducers. In anembodiment the plurality of transducers used to receive theacoustic-generated ultrasound and the separate plurality of transducersused to receive the optoacoustic return signal each comprise at least256 transducers. In an embodiment, the transducers used to receive theoptoacoustic return signal have a wider band frequency response thanseparate transducers used to receive the acoustic-generated ultrasound.In such an embodiment, the transducers used to receive the optoacousticreturn signal have a frequency response from at least about 1 MHz to 5MHz, and more preferably, from about 100 KHz to about 10 MHz, and evenmore preferably from about 50 KHz to about 20 Mhz. In such anembodiment, the transducers used to receive the optoacoustic returnsignal may use high impedance amplifiers, such as 1 KΩ or more, and morepreferably, 5 KΩ or more. In such an embodiment, the transducers used toreceive the acoustic-generate ultrasound would use amplifiers having animpedance of less than 1 KΩ, and more preferably about 200Ω. The use ofseparate transducers would eliminate the need for relay system 110, andthe switching of the transducer outputs thereby between the optoacousticprocessing and overlay system 140 and the ultrasound instrument 150.

As discussed above, in an embodiment, the same transducers are used toreceive acoustic-generated ultrasound and to receive the optoacousticreturn signal. Where the same transducers are used to receiveacoustic-generated ultrasound and to receive the optoacoustic returnsignal, amplifiers should be used that have an impedance within therange of about 1-10 KΩ, and more preferably amplifiers should be usedthat have an impedance of approximately 5 KΩ.

In an embodiment, the sampling of an optoacoustic return signal isperformed in a variable manner, where the gain of the amplifiersassociated with each of the sampled channels is adjusted over time, andis hereinafter referred to as time gain compensation or TGC. TGC rampsup gain on the acoustic input as the optoacoustic return signal becomesfainter, thus more accurately sampling the signal, and providing morenormalized collected data and maintaining good signal-to-noise ratio asthe signal become fainter. Optoacoustic return signal becomes fainterwith time for several reasons, including that the later optoacousticreturn signals have generally traveled further. Thus, generallyoptoacoustic return signal becomes fainter as the depth of a targetincreases. However, the magnitude (and thus needed gain) of optoacousticreturn signals are also affected by the location and source ofillumination. Generally, less light penetrates to deeper depths, andthus, the optoacoustic return signals are fainter because anoptoacoustic event occurring at the surface of a volume generallyinduces a smaller response at a deeper depth. TGC is utilized tocompensate for the later, fainter optoacoustic return signals.

The optoacoustic device 100 may comprise sensors (not shown) that canmeasure power and from that infer both total and peak power of the lightsubsystem 129, and performance and efficiency of the optical path 132.In an embodiment, sensors such as photo detectors can be placed withinor in close proximity to the light subsystem 129 and within or in closeproximity to the probe 102. In each case, the sensors would take ameasurement during the illumination of a light 130, 131 which can beused to infer total and peak power. For this purpose, one or moresensors can be placed inside the probe 102 to measure reflection fromthe optical window. Similarly, one or more sensors can be placed withinthe light subsystem 129 to measure light reflected therein. Deviationover time in the measurements inferred between the two sensor locationsmay be indicative of anomalies in the light path 132.

Discussing now an embodiment of the system having sensors (not shown)such as photo detectors within or in close proximity to the probe 102.In an embodiment, one or more sensors may be placed within the probe, inthe gap 1802 to measure reflection from the optical window.Alternatively, or additionally, in an embodiment, one or more sensorsmay be provided light directly from a component of the light path 132,such as from one or a small plurality of the optical fibers that make upthe light path 132. Alternatively, or additionally, in an embodiment,one or more sensors may be provided light by another path providedwithin the probe. Thus, for example, one or more sensors could belocated within the end of the probe opposite the optical windows 1603,and an auxiliary light path (not shown) can e.g., carry light directlyfrom the light path 132 or reflected from the optical window orotherwise, to the one or more sensors. Alternatively, or additionally,in an embodiment, one or more sensors may be arranged to detect lightoriginating in the light path 132 after it has been reflected from thesurface of three-dimensional volume 160. Using information from sensorsarranged to detect light reflected from the surface of three-dimensionalvolume 160, in combination with information concerning the lighttransmitted through the optical window 1603 towards the volume 160 (suchas information from sensors measuring output from the light subsystem129 or from the optical window 1603), can provide diagnostic informationconcerning the volume 160. Such diagnostic information may include theabsorptiveness, or the darkness, of the volume 160.

In an embodiment, the foregoing sensors can be tuned to specificwavelengths through the use of an optical filter. Thus, for example,sensors within or in close proximity to the probe 102, sensors within orin close proximity to the light subsystem 129, sensors receiving lightfrom an auxiliary light path and/or sensors arranged to detect lightreflected from the surface of the volume 160, can be filtered todiscriminate between the wavelengths of light produced by the lightsubsystem 129 and/or any extraneous light. Accordingly, sensors may beprovided to detect (or potentially to reject) specific lightfrequencies, such as the light from one of the two light sources 130,131.

In an embodiment, one or more sensors within or in close proximity tothe probe 102 can be used as part of a triggering system and method forstarting detection optoacoustic return signal data. In such a triggeringsystem or method the detection of a specific threshold value of light bythe one or more sensors can send a detection control signal to thecomputing subsystem 128. In an embodiment, the detection control signalis sent over the power and control signal lines 109 to the optoacousticprocessing and overlay system 140. The detection control signal is usedby the computing subsystem 128 to initiate (after any appropriate delay,if any) the process of obtaining the optoacoustic return signal data,for example, by “sampling” data from the ultrasound transducer elements.As discussed above, because the one or more sensors can be opticallyfiltered to detect specific light frequencies, the detection controlsignal may be specific to one or more frequencies of light, and mayinitiate differing sampling rates, or delays, based upon the differentfrequency of light.

In an embodiment, one or more sensors within or in close proximity tothe probe 102 can be used as part of a system and method for safelystarting the optoacoustic system 100 and then bringing the laser to itssafe power potential. Although laser light sources (e.g., 130, 131)generally have a controllable power output, many factors can affect thetotal power output by a light source regardless of its setting. Ambienttemperature, for example, may affect the power output by a laser.Similarly, fluctuations in electrical power can also affect the poweroutput by a laser. In addition, the light path 132 can negatively affectthe light output of laser light sources (e.g., 130, 131). Fibers withinthe light path 132 can burn out, or lose transmissive properties as theyage or are used. Moreover, fibers that are positioned in a bend can losetransmissive properties. Thus, the setting of a light source (e.g., 130,131) to a particular output level is not necessarily determinative ofthe light that reaches the other end of the light path 132, andultimately, the volume 160. Accordingly, in an embodiment, the lightsource (e.g., 130, 131) is set to a relatively low power. The relativelylow power should be selected to be a power that, in the event everythingis functioning at its peak output or transmissiveness, would not exceeda desired maximum fluence on the volume 160. Once the light source(e.g., 130, 131) is pulsed, a measurement from the one or more sensorsis used to infer the fluence of light delivered to the volume 160. Inthe event that this inferred fluence is lower than the desired fluencelevel (or a desired range of fluence levels), the output from the lightsource can be increased, and the process repeated. Likewise, in theevent that the inferred light fluence is higher than a desired maximum,the output from the light source can be decreased. Because the system100 is capable of a significant number of laser events per second, therate of increase to the light output, and thus, the potential increasein the fluence level between laser events, can be kept relatively small.In an embodiment, the amount of change in output from the light sourcemay be larger when the inferred fluence is farther away from the desiredfluence level (or a desired range of fluence levels), and smaller whenthe inferred fluence is closer to the desired fluence level.

In addition to providing a method for safely starting the optoacousticsystem and bringing the laser to its safe power potential, the sameprocess can be run as a closed loop control to ensure that the laserfluence is being monitored and controlled, and that to the extent itexceeds a predefined threshold such coming within some margin of asafety limit, its output power can be lowered. Similarly, operating theprocess as a closed loop control can also ensure that the laser outputis being set to a maximum desirable setting even as the operatingconditions of the system 100 (e.g., ambient temperature and electricalpower) change, and regardless of the existing or changing condition ofthe light path 132. Keeping the laser at or close to its highest safelevel permits the largest light fluence, and thus, strongest opticalreturn signal. In an embodiment, one or more of the following: thetarget fluence level, the acceptable hysteresis around the targetfluence level and a maximum fluence level, are user selectable, and whenselected can be used by the processing running as a closed loop controlto maintained the laser as specified. The closed loop control processcan be used to normalize pulse-to-pulse power output.

In an embodiment, where the measurement taken at the one or moreprobe-proximate sensors falls below a predetermined threshold for agiven laser output, as a failsafe, the lasers may be shut down. Such alevel may reflect a failure or detachment of the light path 132, orother unsafe condition.

In an embodiment having one or more sensors within or in close proximityto the probe 102 and one or more sensors within or in close proximity tothe light subsystem 129, the sensors can be utilized as part of a systemfor and method to detect faults in the light path 132 or to provide asafety control for faults in the light path. In an embodiment, the lightoutput of the light subsystem 129 would be expected to be proportionalto the light output of the light path 132 and the light fluence exitingthe optical windows 1603. The use of one or more lightsubsystem-proximate sensors can permit detection of differences in theexpected amount of the light incident on the several sensors. Asdiscussed above, the light path 132 can negatively affect the lightoutput by of laser light sources (e.g., 130, 131). For example, thelight path 132 can be negatively affected by burn out, old or brokenfibers within the bundle. Thus, setting a light source (e.g., 130, 131)to a particular output level is not necessarily determinative of thelight that reaches the other end of the light path 132, and ultimately,the volume 160. By employing both one or more light subsystem-proximatesensors and one or more probe-proximate sensors, performance of thelight path 132 can be detected and monitored.

In an embodiment, the one or more light subsystem-proximate sensors areused to measure the power of the light entering the light path 132 andone or more probe-proximate sensors are used to measure the power of thelight that has been transmitted through the light path 132. Themeasurement taken at the one or more light subsystem-proximate sensorsmay be used to predict a measurement at the one or more probe-proximatesensors. In an embodiment, deviation from the predicted measurement atthe one or more probe-proximate sensors can be used to identifypotential problems with the light path 132. In an embodiment, the sensorreadings are recorded with other data concerning the event. In anembodiment, deviations are assessed to determine whether action needs tobe taken, for example, whether the user needs to check the light path132 connections, or whether the light path 132 is in need of maintenance(e.g., straightening, cleaning, lapping and polishing or othermaintenance) or even replacement. In an embodiment, where themeasurement taken at the one or more probe-proximate sensors deviatesfrom its predicted measurement by more than a predetermined amount, as afailsafe, the lasers may be shut down. Such a deviation may represent afailure or detachment of the light path 132 or other fault or unsafecondition.

In an embodiment having one or more sensors within or in close proximityto the probe 102 and/or one or more sensors within or in close proximityto the light subsystem 129, the measurements from the sensors, alongwith the other settings of the machine (including the commanded lightoutput) should be stored with the data other data associated with thelight pulse, such as the optoacoustic return signal.

In an embodiment, a calibration phantom comprising one or more embeddedphotosensitive sensors is provided. As with the above-described sensors,the sensors in the phantom can be used to infer total and peak power, aswell as light distribution. Deviation over time in the measurementsinferred between the phantom sensors and the other sensors may similarlybe indicative of anomalies. Moreover, changes over time between thereadings of the various sensors within the phantom or within the probemay be indicative of issues with the evenness of light output of theprobe. The use of such sensors rather than the system transducers avoidsacoustic involvement, thus eliminating error introduced by thetransducers themselves.

In an embodiment, a second calibration phantom may be provided withacoustic targets rather than sensors. The use of such a phantomeliminates any error that may be introduced by the sensors themselves.Calibration using both the acoustic target and sensor phantoms wouldprovide a cross-check and mitigate the potential for calibration error.Time gain compensation must be properly calibrated.

In yet a further embodiment, linear or non-linear arrays may bephysically separated from each other, but the data there-from may berecovered in response to the same optoacoustic event. Turning to FIG.26, as an illustrative example, a two-armed (or more) forceps-like probe2600 may contain linear or non-linear transducer arrays 2620 extendingfrom arms 2615 that can be physically positioned using finger grips2605, 2610 at the time of use, for example, on each side of a volume tobe irradiated. In another example (not shown), two or more of thefingers of a glove could contain linear or non-linear arrays oftransducers which can be manually positioned. In each case, althoughpreferable, it is not necessary to know the orientation of one arraywith respect to the other in use. And while it is necessary that theoptoacoustic event irradiate the volume sufficiently to permit the atleast a portion of the transducer arrays coupled to the volume to detectan optoacoustic return signal, it is not necessary that the optoacousticevent is generated from the probe.

Turning to FIG. 27, a forceps-like probe 2700 for use in generating anoptoacoustic image by acquiring data in a forward transmission mode isshown. The probe 2700 may contain a linear or non-linear transducerarray 2720 situated across from an optical window 2730 that can projectlight output from a suitable light source such as a laser. Theseparation of the optical window from the transducer array mitigatesnumerous sources of noise that interfere with the sampling process ofthe optoacoustic return signal.

Each transducer in probe 102 may exhibit slight variations in operation.Accordingly, in an embodiment, once completed, probe 102 is tested inconnection with one or more known test subjects such phantoms (see FIGS.7-9) and the probe's measured response from the test subject isrecorded. In an embodiment, the test subjects will produce a knownoptoacoustic return signal, either in response to a known optoacousticevent, or, by active control of the phantom. Variation from theknown/expected optoacoustic return signal can be identified, andassociated with each specific channel (e.g., transducer) comprising thevariation. In this manner, the probe's own response characteristics—tothe extent they may differ from probe to probe—can be accounted for, andmay be normalized in later processing. Thus, if a particular transducerproduces a signal that differs from the expected signal, that differencecan be accounted for, and then later normalized.

In an embodiment, information associated with a probe's own responsecharacteristics may be stored within the probe itself, and can bereported to the optoacoustic processing and overlay system 140 via powerand control signal lines 109. In an alternative embodiment, informationassociated with a probe's own response characteristics may be storedoutside the probe, and can be associated with a serial number or otheridentifier of the probe. The optoacoustic processing and overlay system140 can obtain the probe response characteristics after identifying theprobe for use. In an embodiment, the probe response characteristics maybe stored in an network accessible location, either on a local disk,network, or on the Internet, and are made accessible to the optoacousticprocessing and overlay system 140 via a connection (not shown) to thatdisk, network or the Internet. In an embodiment, the optoacousticprocessing and overlay system 140 would obtain a unique identifier fromthe probe, and would thereafter query a database on the local device,network, or over the Internet, to obtain response characteristics forthe probe associated with the unique identifier. Probe responsecharacteristics may be recorded and stored at or near the time the probeis manufactured. In an embodiment, probe response characteristics may beupdated by running a specialized test on the probe—the test having aknown/expected response.

The probe identifier may be obtained by the optoacoustic processing andoverlay system 140 after machine startup, but before engaging the lightoutput. In an embodiment, the probe identifier is recorded on a bar codeon the probe, and the bar code is scanned prior to the device causinglight output. In an embodiment, the probe identifier is recorded on acomputer-readable memory in the probe, and is queried by, or reported tothe optoacoustic processing and overlay system 140 after startup, butprior to engaging the light output.

Because the probe identifier is known, the device can maintainstatistics of probe usage. For example, in an embodiment, the device maymaintain statistics of the operation of the probe in optoacoustic mode,including, e.g., the number and type of light output events that haveoccurred, and the number of ultrasound events that have occurred.Statistics can also be maintained concerning total light energy outputfrom the probe (which may be deduced from an internal optical sensor,not shown). In an embodiment, the response characteristics of the probeand the probe statistics can be available to any device 100 on which theprobe 102 is mounted. Thus, for example, such characteristics andstatistics can be stored in a manner that they are accessible over theInternet. In an embodiment, a VPN is used for security on the Internet.

In an embodiment where the light path 132 is fixedly attached to theprobe 102, the probe usage statistics may also be relevant to the fiberoptics. For example, the fibers in the light path 132 may degrade withtime and/or use resulting in some loss of transmission, e.g., broken orburned fibers. Accordingly, in an embodiment, the device can maintainstatistics relevant to total light energy, peak light energy and thenumber of pulses passed through a light path 132. In an embodiment,sensors in the probe can detect information about the energy output ofthe light path, and sensors in the light subsystem 129 can detectinformation about the energy output of the light subsystem 129. Bydetecting variation in the sensors at the two ends over time,maintenance issues can be identified. For example, seeing a decrease atthe probe-side sensors relative to the light subsystem-side sensors mayindicate a that the light path 132 is degrading and needs replacement.Moreover, a specific difference between the probe-side sensors and thelight subsystem-side sensors may result in a condition that causes thedevice 100 to indicate that it is in need of maintenance. In anembodiment, where the difference is greater than a specific safetythreshold, the device 100 may fail to continue to emit light events. Inan embodiment, the information reported by these sensors may be storedwith the usage statistics.

In an embodiment where the light path 132 is completely or partiallydetachable from the probe 102, the detachable portion of the light pathmay have its own unique identifier. Where the detachable portion of thelight path has its own unique identifier, usage statistics that relateto that portion of the light path may be maintained in much the samemanner as the usage statistics for the probe, but associated with thelight path or portion.

One use of the device 100 is performing imaging examinations on humansfor breast cancer detection. A clinical device 100 may be amultimodality system incorporating optoacoustic imaging capability andultrasound imaging capability. An advantage of optoacoustic imaging overultrasound imaging alone is that it provides very high contrast imageswhich may provide for the direct functional evaluation of tumors.

A block diagram of an embodiment of the clinical system is shown in FIG.28 that illustrates the interaction between major subsystems and thetype of signals they represent. In an embodiment, device 100 provides anintegrated system consisting of the following subsystems: ultrasoundsubsystem 2802, optoacoustic electronics subsystem 2804, power supplysubsystem 2806, probe 102 and illumination/laser subsystem 2808, whichmay be housed in one console, and the control and display subsystem 2810that can be attached to a console. The ultrasound subsystem 2802, theoptoacoustic electronics subsystem 2804 and the control & displaysubsystem 2810 will be referred to hereinafter collectively as the UOA.

The ultrasound subsystem 2802 may be, e.g., a fully functionalstand-alone ultrasound system. The ultrasound subsystem 2802 includes anultrasound transmitter 2812 that outputs an ultrasound signal that isused to stimulate tissue. The ultrasound transmitter 2812 provides itsoutput to a relay board 2814 in the optoacoustic electronics subsystem2804 which switches the ultrasound signal to the probe 102. Theultrasound subsystem further includes a data acquisition board, or DAQ,that receives ultrasound signals from the relay board 2814 and processesthem for transmission to and further processing by a computer 2816. Thecomputer 2816 provides signal processing, user interface, and commandand control functionality through software. The computer 2816 includesone or more computer-readable medium for storage of programming as wellas data generated by the system. The computer-readable medium may be inthe form of volatile and/or non-volatile RAM, ROM, solid state drive,optical media, magnetic media (e.g., hard drive) or other storagedevice. The memory and storage may be integrated into or physicallyseparate from the remaining components of the computer. The computer2816 further receives and transmits command and control signals to theDAQ for control of the data acquisition process and the ultrasoundtransmitter.

The optoacoustic electronics subsystem 284 includes a relay board 2814that provides switching functionality for alternately switching receivedultrasound signals to the DAQ of the ultrasound subsystem 2802 andreceived optoacoustic signals to a digital acquisition and processing(DAP) board 2818. The relay board 2814 includes firmware for bothswitching control and timing control. In an embodiment, flex circuitsthat form ultrasound transducers for both transmitting and receivingultrasound signals are integrated into the relay board 2814. The DAP2818 receives and processes the OA signal and outputs processed OAsignals to the computer 2816. The computer 2816 provides command andcontrol signals via a backplane to the DAP 2818 and the relay board2814, and provides timing signals via the backplane to theillumination/laser subsystem 2808.

FIG. 29 shows a block diagram illustrating the illumination subsystem2808 and control interfaces of the system 100 in accordance with anembodiment thereof. Triggers are TTL positive for activation. Some ofillumination subsystem external control and interfaces includeinterlocks, photo diode based outputs (6), grounds, RS232, power andoptical port.

FIG. 30 shows a pulse diagram illustrating a radiation restriction inthe system 100.

In an embodiment the device 100 uses a hand held probe 102 including anarray of transducers and an opening through which laser light can pass.In use, an operator manipulates controls and views the display as theymove the probe 102 over the body or other volume to identify criticalimage characteristics. In an ultrasound mode the laser light source hasno emission. In an optoacoustic mode the laser emits light according tospecific preconfigured and/or operator set up parameters. In anembodiment the hand held probe may be manipulated in a similar fashionto the manipulation of an ultrasound probe. In an embodiment, the device100 includes an operator selectable operational mode whereby anoptoacoustic mode and ultrasound mode are interlaced.

In an embodiment the clinical device 100 includes an illumination source1408 capable of providing two output wavelengths according to specificpreconfigured and/or operator set up parameters. In an embodiment, theoperator will be able to select either an Nd:YAG laser output at 1064 nmor an Alexandrite laser output at 757 nm, or to select the use of bothlaser outputs. When two wavelengths are selected, the laser subsystem,according to specific preconfigured and/or operator set up parameters,may alternate between the two wavelengths one after the other, or inother preconfigured or operator set up cycles. In an embodiment, laseroperating parameters such as energy, pulse rate, and wavelength will beoperator selectable, and subject, however, to specific preconfiguredparameters.

In an embodiment, communication of the laser energy will be via a fiberoptic bundle with a detachable mechanism. The detachable mechanism forinterfacing the laser output to the fiber optic bundle includes a safetyinterlock/laser shutdown if disconnected. In an embodiment, the lasersubsystem components include heat exchangers; pulse drivers; directlaser controls; laser power supplies; laser power management; laserhead(s), cavities and optics; control and drive electronics; electronicinterface ports; and a laser output port.

In an embodiment, the laser is completely controlled by the UOA controlsystem. The clinical device may be powered ON/OFF by the use of a lowcurrent key switch located near the user control panel. Through theaction of this low current switch, closure will cause the secondaryoutput of an isolation transformer's 230 VAC to be applied to each ofthe subsystems, including the laser. Opening this switch removes powerfrom each of the subsystems.

In an embodiment, the laser subsystem consists of a Q-Switched Nd:YAGlaser and an Alexandrite Q-Switched laser with a common concentricoutput connector designed to have a fiber optic bundle attached. Itcontains all necessary electronics, cooling, power management, optics,and connections necessary to meet operational requirements.

As discussed above, according to specific preconfigured parameters, inan embodiment the operator will be able to select the clinical device100 laser light output from the Nd:YAG (1064 nm) only or select laserlight output from the Alexandrite (757 nm) only or alternating the laserlight output of both wavelengths. In an embodiment, selection will beaccomplished via RS232 commands from the UOA.

In an embodiment, the time between wavelength changes will preferably beless than 0.05 seconds, and the time delay to initiate the response to awavelength change shall be less than 0.01 seconds (which is included inthe 0.05 seconds to change wavelengths). This would allow a command tobe 0.01 seconds before the actual wavelength change is made. Thesetiming parameters will permit the device 100 to be capable ofalternating the wavelength output at a rate up to 20 times per second soas to interleave each separate wavelength operating at 10 pulses persecond.

In an embodiment, the laser output pulse width for the Nd:YAG laser isapproximately 7 ns but as long as practical, and in any case should beless than 25 ns for the best pulse stability. The laser output pulsewidth for the Alexandrite laser may be less than approximately 60 ns andmore preferably less than approximately 50 ns. In an embodiment, nosatellite pulse (a secondary laser pulse occurring shortly after theprimary pulse) is allowed for either laser. As discussed above, in anembodiment, one or more light sources other than the Nd:YAG orAlexandrite lasers may be employed. Thus, for example, in an embodiment,one quickly tunable laser could be deployed to create two or moreseparate wavelengths in sequential light pulses during operation of thedevice.

The pulse rate may be operator selectable. In an embodiment, the pulserate is operator selectable from 2, 5, 10 PPS for each wavelength, andwhen interlace is selected the pulse rate will double to 4, 10, 20 PPS.In an embodiment, the maximum time to select between pulse rates will be10 seconds. The pulse rate for each laser wavelength will be independentof single wavelength or interlace operation.

In an embodiment, the energy per pulse (laser output) that will bedirected into the fiber bundle will be variable between 25 mJ to 250 mJin a minimum of 15 steps for each wavelength. In an embodiment, thecontrol will be via the RS232 port. Energy per pulse will beindependently adjustable for each wavelength. In an embodiment, themaximum time for the output energy to be affected post selection will beapproximately 2 seconds.

It is desirable to minimize the unintended pulse-to-pulse variation.Accordingly, in an embodiment, the (uncontrolled) pulse-to-pulse energyvariation will be less than 3% RMS from the output of either laser after50 laser pulses.

In an embodiment, a measure of the output energy of each pulse (bothwavelengths) will be made and will be communicated with an analog outputpulse to the UOA. In an embodiment, the pulse will be a stretchedrepresentation of the optically detected pulse. The amplitude will be arepresentation of the energy of each output pulse. In an embodiment, theamplitude will be 0 to 5 V peak with 5V peak equal to the maximum energyexpected. In an embodiment, the driver for these signals may be DCcoupled throughout and drive a 1000 ohm termination with 0 to 5 Volts.In an embodiment, the pulse may be peak detected and stretched by atleast 200 ns but the peak must occur before 2 us to permit, that atleast two samples are captures, when employing a 6.8 MHz anti aliasingfilter at 20 M samples/sec. In an embodiment, a 20 M samples/secsampling unit is located in the UOA electronics. Interface connectorsmay use BNC on the laser subsystem. The connector output can be providedon either a single BNC connector or a pair of BNC connectors,

In an embodiment, each rising edge of the laser pulses will be detectedand communicated to the UOA in a TTL format over a coax cable with a BNCconnector. In an embodiment, separate signals, coax cables and connectormay be used for each additional wavelength. In an embodiment, the signalwill be a positive going TTL signal that will have a duration of atleast 1 microsecond. In an embodiment, the UOA termination will be ACcoupled into 50 Ohms.

In an embodiment, there will be a sync pulse jitter test. The test mayuse an oscilloscope with the trigger using the TTL sync pulse. The inputwill be the output of a wideband optical test detector that is samplingthe output of the laser pulse. The RMS jitter of the optical detectedwaveform is preferably less than about 6 ns.

In an embodiment, each detected optical pulse for each wavelength ismade available at two test connectors external to the laser system. Inan embodiment, the test connectors will be BNC connectors, and thedrivers for the signals should be able to drive a 50 Ohm scope load.These test signals may be used to support system testing and evaluation.In an embodiment, there is a separate output for each wavelength fromthe sync detectors to an analog driver for a 50 ohms output load—theamplitude can be a percentage of the actual pulse out of the opticaldetector.

In an embodiment, a fiber optical bundle interfaces to the output of thecombined laser output port. In an embodiment, the optical output will behorizontal at the front-right of the optical unit. A quick disconnectconnector may to be used to connect the fiber bundle to the laser outputport.

In an embodiment, the mount for the fiber cable provides self-alignmentto the laser energy output. In an embodiment, a ceramic disk with a 6 mmcentered aperture will be installed at the output of the fiber opticmount to minimize damage to the fiber bundle. In an embodiment, a microswitch is engaged when the fiber bundle has made connection. The microswitch functions as a safety interlock and is used to ensure that thelaser cannot be fired unless the micro switch is closed.

In an embodiment, the laser output beam shape will be circular. In anembodiment, the beam profile will be flattened to approximate a top hatshape to ensure homogeneous illumination of the optical fiber. In anembodiment, the beam width will be 6 mm in diameter at the 10% level.For safety and consistency, the beam shape should not substantiallydeviate from this shape; in an embodiment, the beam shape does notdeviate from this shape by more than 3% RMS over time and frompulse-to-pulse.

In an embodiment, the output of each laser will be approximately 6.25 mmonto the fiber optics, and the beam should not have hot spot(s),including after extensive use. In an embodiment, both beam shapes (forthe Nd:YAG and the Alexandrite) will be equal in diameter to within 5%of the 6 mm diameter. For the purposes herein, a hot spot is defined asa 15% variation in energy density over any 2 mm segment of the beamcross section. In an embodiment, the laser beam must be aimed at theoutput connector such that 98% of the output energy is transmitted intothe fiber cable. In an embodiment, a mechanism is provided for achievinglaser beam alignment in the field.

In an embodiment, the laser spectral width will be less than 30 nm atthe FWHM (Full Wave Half Maximum) level, and the spectralcharacteristics are preferably stable and do not vary frompulse-to-pulse by more than 3 nm RMS.

In an embodiment, the major operating modes of the clinical device 100are:

-   -   a. Off mode: where all power has been turned off and no current        should be flowing within the laser subsystem. This can be        accomplished by turning OFF the main circuit breaker or by        turning the power key switch to off. In this case power may        still be connected to the isolation transformer.    -   b. Sleep mode or ultrasound only mode: Almost all power is shut        down for all operations but with sufficient energy to place the        laser subsystem into the “on” mode. For example only the laser        control unit is power up.    -   c. On Mode: Warm Up Period: Places all necessary power ON to        allow the laser to be warmed up. The laser will measure and        report to the UOA the laser head temperature. Once the laser        head temperature has reached a pre determined value the UOA will        place the laser system into the “standby mode”. In an        embodiment, the laser subsystem will not be allowed to go into        the “standby mode” until sufficient warm up has occurred.    -   d. Standby Mode: Allows the laser to be placed into the “ready        mode” quickly from a Ready Mode command.    -   e. Ready Mode: Places the laser into the emission mode but the        shutter remains closed. In an embodiment, the emission mode can        be started a pre-specified interval, e.g., within 1 second or        after 20 pulses, after the emission mode command.    -   f. Emission mode: Provides specified output energy for as long        as this mode is commanded. In this mode the laser provides for        its lamp sync and driver, the Q-Switch delay and driver and the        pulse rate as determined from external command. The wavelength        output will be as determined from external command.

In an embodiment, the laser subsystem will have the capability to gofrom any operating mode to any lower operating mode directly: “off”being the lowest operating mode and “emission” being the highestoperating mode. For example, in an embodiment, the operator will be ableto go from the emission mode to the standby, on, sleep or off modedirectly. Preferably, the operator will not be able to go from off toemission directly without first going through the modes between.

In an embodiment, the laser will operate with internal synchronism andthe UOA will derive its synchronism from the laser via it sync signaloutputs. In an embodiment, time sensitive interfaces (synchronismsignals) will be interfaced using TTL signals, while computer interfaceinformation will be via RS232 interface. In an embodiment, thewavelength selection mode (single YAG, single ALEX, interlace mode) willbe selected via RS232 and the control unit will produce the internalcommands in interlace or single mode with the right timing. In anembodiment, electronics will validate the present laser emission thruenergy photodiode and/or sync pulses and/or Q-Switch TTL sync outputs.

In an embodiment, a shutter will open to allow laser light to be emitted(defined as the emission mode). In an embodiment, the shutter willremain closed unless two conditions exist—a foot switch closure and anRS-232 command. But, as long as the foot switch remains closed and anRS232 command exists the emission will exist. Both the foot switchclosure and the RS232 must both be present to achieve emissions. Thefoot switch closure may provide within the switch a double contact, NCand NO using a three-wire interface as shown in FIG. 31. When either orboth the foot switch and RS232 command is changed emission will cease toexist via a closure of the shutter, preferably within about 0.5 seconds.The laser subsystem may remain in the Ready mode until commandedotherwise.

In an embodiment, the laser operating system shall keep a non-volatiletime-stamped record of error codes, of lamp shots, and operationalevents, for the purpose of accountability and troubleshooting. Thenon-volatile record may be readable, and possibly erasable, via RS-232commands. In an embodiment, erasure of the non-volatile record requiresa password or other access device. In an embodiment, a log consisting ofnot less than 50 events may be sufficient. In an embodiment, the UOA canpoll the number of messages and read them.

In an embodiment, the laser subsystem will monitor the temperature ofthe lasers heads and report each to the UOA on a periodic basis,permitting the UOA to avoid instructing the laser to go into the ReadyMode unless the laser head has reached an acceptable temperature, andautomatically placing the laser subsystem into the off mode if thetemperature is unexpectedly outside of its appropriate operating range.

In an embodiment, wires to pockels cell and all internal high radiatedsignals should be shielded. To mitigate electromagnetic radiation duringthe imaging time of the clinical device 100, the lamp driver rechargingshould be delayed by more than 70 microseconds after the Q-Switch. SeeFIG. 16. During recharge the electromagnetic radiation must besufficiently low so as not to interfere with ultrasound or OA imaging.

In an alternative embodiment, a control signal can be used to suppresspower supply switching noise during OA data acquisition, and also duringUS data acquisition. For example, a TTL trigger from within the lasercircuitry may be generated such that a logic HIGH would cause theinternal switching power supply to stop its internal oscillator thatdrives the switching PWM (pulse width modulation) circuitry that powersthe flash lamp circuits, and/or any other switching operation, and whenat a logic LOW would resume normal operation. In an embodiment, thiscontrol may not be asserted for more than certain ON time (e.g., 100microseconds), and to not exceed a certain duty cycle. In an embodiment,a trigger signal could be negative logic wherein a logic LOW would stopthe oscillator and a logic HIGH would allow it to resume. In anembodiment, the trigger signal can be applied to one or more otherswitching power supplies within the laser and./or elsewhere in the OAsystem, which may suppress electrical noise from the power supply duringthe non-oscillatory interval. In an embodiment, the data acquisitionperiod should be within the interval during which the one or moreswitching power supplies have the switching circuitry inhibited. Evenwhere a switching power supply is of a type that is not PWM controlled,the trigger can in any event be used to inhibit operation of theinternal oscillator used to control the switching functions.

In an embodiment, the user interface console will contain a “PanicButton” to place the laser into the off mode by removing all AC power tothe laser system.

In an embodiment, the laser subsystem and all other subsystems willoperate from 230+1-10% VAC, single phases, 60/50+/−3 Hz, 4000 VA max. Inan embodiment, the mains voltage may be isolated from the varioussubsystems by the use of an isolation transformer such as part number925.1202, manufactured by www.toroids.com, or equivalent, and protectedwith a switchable AC circuit breaker on the primary side. The secondaryside of this transformer will provide AC power to each of the four (4)AC powered subsystems through a soft start isolation transformer toavoid inrush current problems. In an embodiment, the laser subsystem isadapted to accommodate a sudden loss of input power or brownout withoutcausing damage, requiring realignment, tuning or causing unsafeoperations.

In an embodiment, all operating system controls may be provided via UOAelectronics.

The present system and methods are described above with reference toblock diagrams and operational illustrations of methods and devicescomprising an optoacoustic probe. It is understood that each block ofthe block diagrams or operational illustrations, and combinations ofblocks in the block diagrams or operational illustrations, may beimplemented by means of analog or digital hardware and computer programinstructions. These computer program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, ASIC,FPGA or other programmable data processing apparatus, such that theinstructions, which execute via the processor of the computer or otherprogrammable data processing apparatus, implements the functions/actsspecified in the block diagrams or operational block or blocks. In somealternate implementations, the functions/acts noted in the blocks mayoccur out of the order noted in the operational illustrations. Forexample, two blocks shown in succession may in fact be executedsubstantially concurrently or the blocks may sometimes be executed inthe reverse order, depending upon the functionality/acts involved.

As used in this description and in the following claims, “a” or “an”means “at least one” or “one or more” unless otherwise indicated. Inaddition, the singular forms “a”, “an”, and “the” include pluralreferents unless the content clearly dictates otherwise. Thus, forexample, reference to a composition containing “a compound” includes amixture of two or more compounds.

As used in this specification and the appended claims, the term “or” isgenerally employed in its sense including “and/or” unless the contentclearly dictates otherwise.

The recitation herein of numerical ranges by endpoints includes allnumbers subsumed within that range (e.g. 1 to 5 includes 1, 1.5, 2,2.75, 3, 3.80, 4, and 5).

Unless otherwise indicated, all numbers expressing quantities ofingredients, measurement of properties and so forth used in thespecification and claims are to be understood as being modified in allinstances by the term “about,” unless the context clearly dictatesotherwise. Accordingly, unless indicated to the contrary, the numericalparameters set forth in the foregoing specification and attached claimsare approximations that can vary depending upon the desired propertiessought to be obtained by those skilled in the art utilizing theteachings of the present invention. At the very least, and not as anattempt to limit the scope of the claims, each numerical parametershould at least be construed in light of the number of reportedsignificant digits and by applying ordinary rounding techniques. Anynumerical value, however, inherently contains certain errors necessarilyresulting from the standard deviations found in their respective testingmeasurements.

Those skilled in the art will recognize that the methods and systems ofthe present disclosure may be implemented in many manners and as suchare not to be limited by the foregoing exemplary embodiments andexamples. In other words, functional elements being performed by singleor multiple components, in various combinations of hardware and softwareor firmware, and individual functions, may be distributed among softwareapplications at either the client level or server level or both. In thisregard, any number of the features of the different embodimentsdescribed herein may be combined into single or multiple embodiments,and alternate embodiments having fewer than, or more than, all of thefeatures described herein are possible. Functionality may also be, inwhole or in part, distributed among multiple components, in manners nowknown or to become known. Thus, myriad software/hardware/firmwarecombinations are possible in achieving the functions, features,interfaces and preferences described herein. Moreover, the scope of thepresent disclosure covers conventionally known manners for carrying outthe described features and functions and interfaces, as well as thosevariations and modifications that may be made to the hardware orsoftware or firmware components described herein as would be understoodby those skilled in the art now and hereafter.

Furthermore, the embodiments of methods presented and described asflowcharts in this disclosure are provided by way of example in order toprovide a more complete understanding of the technology. The disclosedmethods are not limited to the operations and logical flow presentedherein. Alternative embodiments are contemplated in which the order ofthe various operations is altered and in which sub-operations describedas being part of a larger operation are performed independently.

Various modifications and alterations to the invention will becomeapparent to those skilled in the art without departing from the scopeand spirit of this invention. It should be understood that the inventionis not intended to be unduly limited by the specific embodiments andexamples set forth herein, and that such embodiments and examples arepresented merely to illustrate the invention, with the scope of theinvention intended to be limited only by the claims attached hereto.Thus, while the invention has been particularly shown and described withreference to a preferred embodiment thereof, it will be understood bythose skilled in the art that various changes in form and details may bemade therein without departing from the spirit and scope of theinvention.

What is claimed is:
 1. A method comprising: generating a firstparametric map; generating a second parametric map; generating a maskreflective of a combination of information in the first parametric mapand information in the second parametric map, wherein the mask defines aRegion of Interest (ROI); generating a masked parametric map by applyingthe mask to an auxiliary map, thus forming a new parametric map, theauxiliary map being selected from the group comprising: the firstparametric map, the second parametric map, an additional parametric map,and an image; and outputting the masked parametric map; wherein thefirst parametric map and the second parametric map are based upon atleast a portion of at least two optoacoustic images, each of the atleast two optoacoustic images reflecting at least a portion of anoptoacoustic response of a volume of tissue to a different light event,at least one of the different light events having a shorter predominantwavelength than at least one other of the different light events, thefirst parametric map being reflective of areas within at least a portionof the volume of tissue, which areas have a difference in absorption inresponse to a longer predominant wavelength light event compared to theshorter predominant wavelength light event; and the second parametricmap being reflective of areas within at least a portion of the volume oftissue having stronger absorption, in response to the longer and shorterwavelength light events, than other areas within the at least a portionof the volume of tissue.
 2. The method of claim 1, wherein the mask isused to highlight areas of an image.
 3. The method of claim 1, whereingenerating the mask comprises: generating a mathematical function of thefirst parametric map; generating a mathematical function of the secondparametric map; and combining the results of the mathematical functionof the first parametric map and the mathematical function of the secondparametric map by performing an intersection between the mathematicalfunction of the first parametric map and the mathematical function ofthe second parametric map.
 4. The method of claim 1, further comprising;processing the first parametric map to produce a first grayscaleparametric map; and processing the second parametric map to produce asecond grayscale parametric map, wherein said first and second grayscaleparametric maps are each reflective of a single-image-channel map. 5.The method of claim 4, further comprising; analyzing the first grayscaleparametric map to produce a first color parametric map; analyzing thesecond grayscale parametric map to produce a second color parametricmap, wherein each of said first and second color parametric map arereflective of a single channel of a multi-image-channel image map; andcreating the multi-image-channel image map of the ROI by combining thefirst color parametric map, the second color parametric map and themasked parametric map.
 6. The method of claim 5 wherein the maskedparametric map is reflective of a relative level of oxygenatedhemoglobin in at least a portion of a volume of tissue.
 7. The method ofclaim 5, further comprising; generating an order list for the firstcolor parametric map and the second color parametric map; and generatinga color reference point for the multi-image-channel image map.
 8. Themethod of claim 5 wherein the ROI is defined based, at least in part,upon a signal-to-noise ratio (SNR), wherein the SNR is a high SNR value.9. The method of claim 8 further comprising; displaying the maskedparametric map; and limiting the display of the masked parametric map toa region having a high SNR.
 10. The method of claim 1, whereingenerating the mask is performed by using information contained in theat least a portion of each of the at least two optoacoustic imagesrather than from information in each of the first and the secondparametric map.
 11. The method of claim 10, wherein at least one of theat least two optoacoustic images is a first envelope image, and at leastone of the at least two optoacoustic images is a second envelope image,and wherein the method further comprises: generating the first envelopeimage based upon at least a portion of a first sinogram, the firstsinogram comprising data reflecting at least a portion of anoptoacoustic response of the volume of tissue to the light event havinga first predominant wavelength; and generating the second envelope imagebased upon at least a portion of a second sinogram, the second sinogramcomprising data reflecting at least a portion of an optoacousticresponse of the volume of tissue to the light event having anotherpredominant wavelength.
 12. The method of claim 1, further comprising:creating one light event in the volume of tissue, the light event havinga first predominant wavelength; sampling at least a portion of anoptoacoustic response to the one light event, and storing the sampleddata as a first sinogram; creating another light event in the volume oftissue, the light event having another predominant wavelength; samplingat least a portion of an optoacoustic response to the another lightevent, and storing the sampled data as a second sinogram.
 13. The methodof claim 12, further comprising processing the first and secondsinograms prior to generating envelope images based thereupon, theprocessing reducing undesired data in the sinograms, the undesired datacomprising information other than a location and amount of absorption atthe wavelength of the light events.
 14. The method of claim 1, furthercomprising: receiving an ultrasound image representing the at least aportion of a volume of tissue; co-registering and overlaying theultrasound image with the masked parametric map prior to outputting themasked parametric map; and wherein outputting the masked parametric mapcomprises outputting the masked parametric map coregistered and overlaidon the ultrasound image.
 15. The method of claim 14, further comprising:co-registering and overlaying the ultrasound image with the first andsecond parametric maps; and outputting the first and second parametricmaps coregistered and overlaid on the ultrasound image.
 16. A methodcomprising: generating a first parametric map; generating a secondparametric map; generating a mask reflective of a combination ofinformation in the first parametric map and information in the secondparametric map, wherein the mask defines a Region of Interest (ROI);generating a masked parametric map by applying the mask to an auxiliarymap, thus forming a new parametric map, the auxiliary map being selectedfrom the group comprising: the first parametric map, the secondparametric map, an additional parametric map, and an image; outputtingthe masked parametric map; generating a color parametric map thatincludes one or more of a red-image-channel map, a green-image-channelmap, a blue-image-channel map and an alpha-image-channel of an imagemap.
 17. The method of claim 16, wherein generating the mask comprises:generating a mathematical function of the first parametric map;generating a mathematical function of the second parametric map; andcombining the results of the mathematical function of the firstparametric map and the mathematical function of the second parametricmap by performing an intersection between the mathematical function ofthe first parametric map and the mathematical function of the secondparametric map.
 18. The method of claim 16, further comprising;processing the first parametric map to produce a first grayscaleparametric map; and processing the second parametric map to produce asecond grayscale parametric map, wherein said first and second grayscaleparametric maps are each reflective of a single-image-channel map. 19.The method of claim 18, further comprising; analyzing the firstgrayscale parametric map to produce a first color parametric map;analyzing the second grayscale parametric map to produce a second colorparametric map, wherein each of said first and second color parametricmap are reflective of a single channel of a multi-image-channel imagemap; and creating the multi-image-channel image map of the ROI bycombining the first color parametric map, the second color parametricmap and the masked parametric map.
 20. The method of claim 19, furthercomprising; generating an order list for the first color parametric mapand the second color parametric map; and generating a color referencepoint for the multi-image-channel image map.
 21. The method of claim 16wherein the masked parametric map is reflective of a relative level ofoxygenated hemoglobin in at least a portion of a volume of tissue. 22.The method of claim 16 further comprising; displaying the maskedparametric map; and limiting the display of the masked parametric map toa region having a high SNR.
 23. The method of claim 16, wherein at leastone of the at least two optoacoustic images is a first envelope image,and at least one of the at least two optoacoustic images is a secondenvelope image, and wherein the method further comprises: generating thefirst envelope image based upon at least a portion of a first sinogram,the first sinogram comprising data reflecting at least a portion of anoptoacoustic response of the volume of tissue to the light event havinga first predominant wavelength; and generating the second envelope imagebased upon at least a portion of a second sinogram, the second sinogramcomprising data reflecting at least a portion of an optoacousticresponse of the volume of tissue to the light event having anotherpredominant wavelength.
 24. A method comprising: generating a firstparametric map; generating a second parametric map; generating a maskreflective of a combination of information in the first parametric mapand information in the second parametric map, wherein the mask defines aRegion of Interest (ROI); generating a masked parametric map by applyingthe mask to an auxiliary map, thus forming a new parametric map, theauxiliary map being selected from the group comprising: the firstparametric map, the second parametric map, an additional parametric map,and an image; outputting the masked parametric map, wherein the maskedparametric map is reflective of an alpha channel of an image map. 25.The method of claim 24, wherein generating the mask comprises:generating a mathematical function of the first parametric map;generating a mathematical function of the second parametric map; andcombining the results of the mathematical function of the firstparametric map and the mathematical function of the second parametricmap by performing an intersection between the mathematical function ofthe first parametric map and the mathematical function of the secondparametric map.
 26. The method of claim 24, further comprising;processing the first parametric map to produce a first grayscaleparametric map; and processing the second parametric map to produce asecond grayscale parametric map, wherein said first and second grayscaleparametric maps are each reflective of a single-image-channel map. 27.The method of claim 26, further comprising; analyzing the firstgrayscale parametric map to produce a first color parametric map;analyzing the second grayscale parametric map to produce a second colorparametric map, wherein each of said first and second color parametricmap are reflective of a single channel of a multi-image-channel imagemap; and creating the multi-image-channel image map of the ROI bycombining the first color parametric map, the second color parametricmap and the masked parametric map.
 28. The method of claim 27, furthercomprising; generating an order list for the first color parametric mapand the second color parametric map; and generating a color referencepoint for the multi-image-channel image map.
 29. The method of claim 24,wherein the masked parametric map is reflective of a relative level ofoxygenated hemoglobin in at least a portion of a volume of tissue. 30.The method of claim 24, further comprising; displaying the maskedparametric map; and limiting the display of the masked parametric map toa region having a high SNR.
 31. The method of claim 24, wherein at leastone of the at least two optoacoustic images is a first envelope image,and at least one of the at least two optoacoustic images is a secondenvelope image, and wherein the method further comprises: generating thefirst envelope image based upon at least a portion of a first sinogram,the first sinogram comprising data reflecting at least a portion of anoptoacoustic response of the volume of tissue to the light event havinga first predominant wavelength; and generating the second envelope imagebased upon at least a portion of a second sinogram, the second sinogramcomprising data reflecting at least a portion of an optoacousticresponse of the volume of tissue to the light event having anotherpredominant wavelength.
 32. A method comprising: generating a firstparametric map; generating a second parametric map; generating a maskreflective of a combination of information in the first parametric mapand information in the second parametric map, wherein the mask defines aRegion of Interest (ROI); generating a masked parametric map by applyingthe mask to an auxiliary map, thus forming a new parametric map, theauxiliary map being selected from the group comprising: the firstparametric map, the second parametric map, an additional parametric map,and an image; outputting the masked parametric map, wherein the maskedparametric map is reflective of a ROI multi-image-channel image map,wherein the ROI multi-image-channel image map is reflective of anon-contiguous ROI.
 33. A method comprising: generating a firstparametric map; generating a second parametric map; generating a maskreflective of a combination of information in the first parametric mapand information in the second parametric map, wherein the mask defines aRegion of Interest (ROI); generating a masked parametric map by applyingthe mask to an auxiliary map, thus forming a new parametric map, theauxiliary map being selected from the group comprising: the firstparametric map, the second parametric map, an additional parametric map,and an image; outputting the masked parametric map; calculating a meanvalue and standard deviation of the ROI based at least in part oninformation in the first and second parametric maps for the ROI; andgenerating a color reference point based, at least in part, upon themean value of the ROI and an offset, wherein the offset is calculated bydividing a color offset bias parameter by the standard deviation of theROI.
 34. A method comprising: generating a first parametric map based ontwo optoacoustic images, each resulting from an optoacoustic response ofa tissue to different light events including at least a first lightevent having a shorter wavelength than a second light event, wherein theoptoacoustic responses are reflective of a difference in absorption ofthe tissue; generating a second parametric map based on two optoacousticimages reflective of at least a first portion of the tissue having astronger absorption in response to the first and second light eventsthat to a second portion of the tissue; generating a mask reflective ofa combination of a mathematical function of the first parametric map anda mathematical function of the second parametric map, wherein the maskproduces a function for weighting areas of the optoacoustic images todefine a Region of Interest (ROI); generating a masked parametric map byapplying the mask to an auxiliary map, the auxiliary map being selectedfrom the group comprising: the first parametric map, the secondparametric map, and an optoacoustic image, wherein the masked parametricmap is reflective of an alpha channel of an image map; and outputtingthe masked parametric map.
 35. The method of claim 34, furthercomprising; processing the first parametric map to produce a firstgrayscale parametric map; processing the second parametric map toproduce a second grayscale parametric map; analyzing the first grayscaleparametric map to produce a first color parametric map; analyzing thesecond grayscale parametric map to produce a second color parametricmap, wherein each of said first and second color parametric map arereflective of a single channel of a multi-image-channel image map; andcreating the multi-image-channel image map of the ROI by combining thefirst color parametric map, the second color parametric map and themasked parametric map.
 36. The method of claim 34 wherein the ROI isdefined based, at least in part, upon a signal-to-noise ratio (SNR),wherein the SNR is a high SNR value.
 37. The method of claim 34, whereingenerating the mask comprises: generating a mathematical function of thefirst parametric map; generating a mathematical function of the secondparametric map; and combining the results of the mathematical functionof the first parametric map and the mathematical function of the secondparametric map by performing an intersection between the mathematicalfunction of the first parametric map and the mathematical function ofthe second parametric map.
 38. The method of claim 34, furthercomprising; processing the first parametric map to produce a firstgrayscale parametric map; and processing the second parametric map toproduce a second grayscale parametric map, wherein said first and secondgrayscale parametric maps are each reflective of a single-image-channelmap.
 39. The method of claim 38, further comprising; analyzing the firstgrayscale parametric map to produce a first color parametric map;analyzing the second grayscale parametric map to produce a second colorparametric map, wherein each of said first and second color parametricmap are reflective of a single channel of a multi-image-channel imagemap; and creating the multi-image-channel image map of the ROI bycombining the first color parametric map, the second color parametricmap and the masked parametric map.
 40. The method of claim 34, whereinthe masked parametric map is reflective of a relative level ofoxygenated hemoglobin in at least a portion of a volume of tissue. 41.The method of claim 39, further comprising; generating an order list forthe first color parametric map and the second color parametric map; andgenerating a color reference point for the multi-image-channel imagemap.
 42. The method of claim 34, further comprising; displaying themasked parametric map; and limiting the display of the masked parametricmap to a region having a high SNR.
 43. The method of claim 34, whereinat least one of the at least two optoacoustic images is a first envelopeimage, and at least one of the two optoacoustic images is a secondenvelope image, and wherein the method further comprises: generating thefirst envelope image based upon at least a portion of a first sinogram,the first sinogram comprising data reflecting at least a portion of anoptoacoustic response of the volume of tissue to the light event havinga first predominant wavelength; and generating the second envelope imagebased upon at least a portion of a second sinogram, the second sinogramcomprising data reflecting at least a portion of an optoacousticresponse of the volume of tissue to the light event having anotherpredominant wavelength.